Multicarrier sub-layer for direct sequence channel and multiple-access coding

ABSTRACT

Carrier Interferometry (CI) provides wideband transmission protocols with frequency-band selectivity to improve interference rejection, reduce multipath fading, and enable operation across non-continuous frequency bands. Direct-sequence protocols, such as DS-CDMA, are provided with CI to greatly improve performance and reduce transceiver complexity. CI introduces families of orthogonal polyphase codes that can be used for channel coding, spreading, and/or multiple access. Unlike conventional DS-CDMA, CI coding is not necessary for energy spreading because a set of CI carriers has an inherently wide aggregate bandwidth. Instead, CI codes are used for channelization, energy smoothing in the frequency domain, and interference suppression. CI-based ultra-wideband protocols are implemented via frequency-domain processing to reduce synchronization problems, transceiver complexity, and poor multipath performance of conventional ultra-wideband systems. CI allows wideband protocols to be implemented with space-frequency processing and other array-processing techniques to provide either or both diversity combining and sub-space processing. CI also enables spatial processing without antenna arrays. Even the bandwidth efficiency of multicarrier protocols is greatly enhanced with CI. CI-based wavelets avoid time and frequency resolution trade-offs associated with conventional wavelet processing. CI-based Fourier transforms eliminate all multiplications, which greatly simplifies multi-frequency processing. The quantum-wave principles of CI improve all types of baseband and radio processing.

RELATED APPLICATIONS

This application is Divisional of U.S. patent application Ser. No.10/131,163 filed Apr. 24, 2002 which is a Continuation In Part of U.S.patent application Ser. No. 09/022,950, filed Feb. 12, 1998, which isnow U.S. Pat. No. 5,955,992. This application is also a Continuation InPart of U.S. Provisional Application 60/286,850, filed Apr. 26, 2001.

BACKGROUND OF THE INVENTION

I. Field of the Invention

The present invention relates to direct-sequence code division multipleaccess (DS-CDMA), direct sequence spread spectrum (DSSS), andmulticarrier spread spectrum communications. More specifically, theinvention relates to adaptations of Carrier Interferometry (CI) thatgenerate CDMA-like and DSSS-like signals.

II. Description of the Related Art

A wideband signal (such as a DS-CDMA signal) transmitted in a multipathenvironment experiences a frequency-selective fade. If the duration ofthe data bits is smaller than the multipath delay, the received signalsexperience inter-symbol interference resulting from delayed replicas ofearlier bits arriving at the receiver. Improved DS-CDMA systems useinterference cancellation to increase capacity; however, the requiredsignal-processing effort is proportional to at least the cube of thebandwidth. Furthermore, DS-CDMA is susceptible to near-far interference,and its long pseudo-noise (PN) codes require long acquisition times. Forthese reasons, Orthogonal Frequency Division Multiplexing (OFDM) hasbeen merged with DS-CDMA.

An OFDM system using fast Fourier transforms to generate orthogonal waveforms is described in an article by S. B. Weinstein and P. M. Ebertentitled “Data Transmission by Frequency Division Multiplexing Using theDiscrete Fourier Transform,” IEEE Transactions on CommunicationTechnology, Vol. COM-19, No. 5, pp. 628-634, October 1971. In this OFDMsystem, the data symbols are processed in the transmitter by an inversefast Fourier transform and in the receiver by a fast Fourier transform.The symbols are time-limited and the subcarriers overlap in thefrequency domain.

OFDM has a high spectral efficiency (the spectrum of the subcarriersoverlap) and combats frequency-selective fading. However, the amplitudeof each carrier is affected by the Rayleigh law, hence flat fadingoccurs. Therefore, good channel estimation with an appropriate detectionalgorithm and channel coding is essential to compensate for fading.Coded OFDM provides data redundancy to reduce probability of error, butat the expense of reduced bandwidth efficiency.

Because frequency diversity is inherent in OFDM, it is much simpler toachieve than in a DS-CDMA system (which requires a Rake receiver toachieve diversity in the time domain). Frequency diversity can exploitall of the reflected energy in a multipath environment whereas atime-diversity (i.e., a Rake) receiver typically combines only a smallfraction of the energy. OFDM systems benefit from a lower speed,parallel type of signal processing. A Rake receiver in a DS-CDMA systemuses a fast, serial type of signal processing, which results in greaterpower consumption. In addition, OFDM simplifies the channel estimationproblem, thus simplifying the receiver design.

In multicarrier CDMA (MC-CDMA), a spreading sequence is converted fromserial to parallel. Each chip in the sequence modulates a differentcarrier frequency. Thus, the resulting signal has a PN-coded structurein the frequency domain, and the processing gain is equal to the numberof carriers.

In multi-tone CDMA, or multicarrier DS-CDMA, the available spectrum isdivided into a number of equal-width frequency bands used to transmit anarrowband direct-sequence waveform. In U.S. Pat. No. 5,504,775, binaryCDMA code symbols are applied to individual carriers in an OFDM system.U.S. Pat. Nos. 5,521,937, 5,960,032, and 6,097,712 describe multicarrierDSSS systems having direct-sequence coding on each subcarrier.

U.S. Pat. Nos. 5,519,692 and 5,563,906 describe geometric harmonicmodulation (GHM) in which preamble and traffic waveforms are createdfrom multiple carrier frequencies (tones). The waveforms comprise tonesincorporating a binary phase code where signal phases are 0 or −π/2. Thebinary phase offsets, which are applied to the tones, provide thespreading codes. The traffic waveforms are products of the tones.Orthogonality of GHM signals is realized upon correlation with areference signal at a receiver. A preamble carrier waveform isconstructed by summing the tones. Therefore, the preamble signals aresimilar to MC-CDMA signals.

GHM uses binary-phase offsets instead of polyphase offsets. Thus, GHMdoes not provide carriers with phase relationships that enableorthogonal superpositions of the carriers. Received GHM signals requireprocessing by a correlator, whereas CI-based signals that are orthogonalin time can be processed using simpler signal-processing techniques,such as time sampling and weight-and-sum. Furthermore, GHM does notachieve the throughput, performance, and adaptability benefits enabledby orthogonal interferometry signals.

U.S. Pat. No. 4,901,307 describes processes of creating marginalisolation, which enhances in frequency reuse in DS-CDMA systems. InDS-CDMA, even small reductions in the overall power level of the systemallow for increased system capacity. One particularly effective methodfor creating isolation and improving frequency reuse is spatial divisionmultiple access (SDMA). SDMA applications to multiple accesscommunications, including adaptive array processing, are discussed inU.S. Pat. No. 5,642,353, U.S. Pat. No. 5,592,490, U.S. Pat. No.5,515,378, and U.S. Pat. No. 5,471,647. In addition to frequency reuse,antenna arrays also provide increased processing gain and improvedinterference rejection.

Adaptive antenna arrays may be implemented with DS-CDMA communicationsto provide significant improvements in range extension, interferencereduction, and system capacity. To identify a particular user, a DS-CDMAsystem demodulates Walsh codes after converting the received signal fromRF to digital. Therefore, an adaptive antenna array requires informationabout the user codes, or it needs to demodulate many different incomingRF signals to track mobile users. These methods are complex processesthat are more difficult to implement than tracking users in non-CDMAsystems. Furthermore, the wideband nature of DS-CDMA signals restrictsthe effectiveness of beam forming, interference nulling, spatialinterferometry multiplexing, and other techniques employed by adaptiveantenna arrays.

U.S. Pat. No. 6,211,671 is one of the earliest references that describeinterference cancellation in a non-beamforming type of array processor.A wideband signal is separated into narrowband signal components tooptimize cancellation efficiency. This decomposition also reducescomputational complexity. Interference cancellation compensates forpropagation-path differences and differences in receiver responses tointerfering multi-frequency signals.

U.S. Pat. No. 6,008,760, which is assigned to the same entity as the'671 patent, illustrates this cancellation method in a communicationsystem that uses multi-element transmitters and receivers to create aplurality of same-frequency spatial subchannels.

U.S. Pat. Nos. 5,671,168 and 5,528,581 describe the application ofwell-known beam-forming processes to OFDM. U.S. Pat. No. 6,144,711describes a simple combination of well-known OFDM and array-processingtechniques.

U.S. Pat. No. 6,128,276 describes an application of antenna-arrayprocessing to well-known “stacked-carrier” spread spectrumcommunications in which duplicates of a data sequence are transmittedover different frequencies to achieve frequency diversity. Random orpseudorandom spreading weights are applied to each frequency band tofacilitate multiple access. These spreading weights, unlike MC-CDMAweights, may provide both amplitude and phase adjustment. However, likeMC-CDMA and other redundantly modulated multicarrier protocols, thespreading weights described in '276 do not enable carrier interferometrynor do they achieve the enormous throughput and performance improvementsenabled by carrier interferometry.

In conventional multicarrier protocols, such as OFDM, DMT, and MC-CDMA,spreading is performed by energizing bins of a fast Fourier transform(FFT). U.S. Pat. Nos. 5,282,222, 6,175,550, and 5,608,764 illustrateexemplary OFDM transceivers. Blocks of coded data bits areserial-to-parallel converted and input into an N-point inverse-FFT(IFFT) operation. The output of the IFFT is parallel-to-serial convertedto produce an OFDM signal having N frequency components. Time-domainsamples of a received OFDM signal are serial-to-parallel converted andoperated upon with an N-point FFT before being parallel-to-serialconverted into a recovered data stream.

The N-point transforms used in OFDM essentially map one set of datasymbols onto another set of data symbols. Each transform of a transformpair provides the basis for mixing symbols together to form a code thatcan be reversed by the complementary transform. In addition to Fouriertransforms, other transform pairs are described in U.S. Pat. Nos.5,282,222 and 6,192,068. This type of coding enables an overlay ofmultiple codes, which is referred to as “multi-code” spread spectrum.

One technique for implementing a Fourier transform includes filtering atime-domain sequence of input symbols. A polyphase FIR filter bank canbe implemented equivalently with an N-point discreet Fourier transform(DFT) or inverse DFT (as illustrated by J. G. Proakis in “Digital SignalProcessing,” 3^(rd) edition, p 825-831). Linear FIR filtering performedvia the DFT typically involves segmenting the input symbols into blocks.The blocks are processed via the DFT and/or the IDFT to produce a blockof output data. Common filtering techniques include the overlap-savemethod and the overlap-add method. The resulting output symbols arecomplex-weighted sums of the input symbols.

Various techniques have been developed to efficiently process Fouriertransform algorithms, such as described in U.S. Pat. Nos. 6,169,723,6,137,839, 5,987,005, 5,297,236, and 5,365,470. However, none of theprior-art Fourier transform techniques provide a means to replacedirect-sequence processing with Fourier transforms or equivalentfrequency-domain operations.

More recently, wavelet theory developed in response to perceivedlimitations to Fourier analysis and windowed Fourier techniques. Likestring theory in quantum mechanics, wavelets provide an effectivemicroscopic basis for describing macroscopic phenomena. However, one ofthe problems with conventional wavelet theory is that it relies on anabstraction with no physical basis to describe physical phenomena. InHubbard's The World According to Wavelets, Meyer states that a Fouriertransform is real, whereas wavelets do not have a physical existence. J.C. Van den Berg states that “wavelets cannot be interpreted in physicalterms as easily as sines and cosines and their frequencies.” This causesa major disconnect between interpretation and reality. As a result,engineers who work with wavelet transforms often have difficulty withthe interpretation. In contrast, the intuitive nature of Fouriertransforms is due to their direct association with real phenomena.

None of the prior-art references implement frequency-domain receptionfor direct-sequence signals. The prior-art references do not enableorthogonal multicarrier processing to be applied to direct-sequencespread-spectrum signals. Conventional direct-sequence protocols are notcompatible with many types of adaptive array processing. The prior-artreferences fail to provide simultaneous improvements of increasedthroughput and enhanced performance to DSSS and DS-CDMA systems. Noprior-art references describe a wave-based signal-processing technologythat radically improves coding, wavelet, and Fourier-transformoperations. None of the prior-art communication and signal-processingalgorithms are based on principles of wave mechanics and quantuminterferometry that describe the fundamental nature of all matter andenergy.

SUMMARY OF THE INVENTION

Carrier Interferometry (CI) is a class of multicarrier-processingtechniques that use sets of phase shifts (i.e., phase spaces) to overlayand separate data streams that are redundantly modulated onto the samesets of carrier signals. Multiple carriers are redundantly modulatedwith data streams that are orthogonalized by virtue of the differentsets of phase spaces encoding each data stream. Interference between thecarriers provides the means to orthogonalize the data streams, whetherthe carriers are combined or processed separately.

CI achieves the benefits of both narrowband and wideband processing.Narrowband processing is simpler than wideband processing. For example,multipath distortions in a narrowband signal can be characterized by asingle attenuation and phase offset. Array processing, such asphased-array, adaptive beam forming, space-time, space-frequency, andspatial-interferometry techniques, are more effective and more easilyperformed with narrowband signals. This is important because arrayprocessing enables frequency reuse via spatial division multiple access,which greatly improves system capacity.

Wideband processing can provide benefits of frequency diversity. Pathdiversity exploits the short symbol length of a wideband signal relativeto multipath delay. Path-diversity processing, such as RAKE reception,coherently combines multiple reflections of a desired signal.Frequency-diversity combining processes the reflected energy moreefficiently, thus increasing transmission range or reducing requiredtransmission power.

CI avoids multipath-interference problems of both wideband andnarrowband signals while appearing like a conventional transmissionprotocol, such as TDMA or DS-CDMA. Inter-symbol interference occurs whena reflected signal travels a distance sufficiently greater than thedistance traversed by a line-of-sight signal so as to cause a delaygreater than the duration of a data symbol. This causes an earliertransmitted data symbol to interfere with a later symbol at a receiver.CI avoids inter-symbol interference by transmitting data symbols onnarrowband carriers. The long symbol duration associated with anarrowband carrier ensures that multipath delays do not exceed thesymbol duration. However, multipath fading occurs when a narrowbandsignal traverses two paths having a half-cycle phase difference.

CI avoids the problem of multipath fading by redundantly modulating eachdata symbol onto multiple carriers that are adequately separated withrespect to frequency. Data symbols will not be lost to multipath fadingif the carriers fade independently. However, redundant modulationtypically reduces bandwidth efficiency.

CI avoids the problem of reduced bandwidth efficiency by modulating upto 2N coded data symbols on each of N carriers. However, conventionalinformation theory shows that multiple signals occupying the samefrequency band and time interfere with each other. Increasedinterference on one or more carriers typically increases probability oferror.

CI avoids the problem of increased interference and probability of errorby exploiting interferometry to orthogonalize data symbols modulated onthe same carriers. Interference on each carrier cancels when thecarriers are combined. This allows desired signals to be separated frominterfering signals via superposition. Thus, CI-based multiple-accessprotocols achieve higher throughput with better signal quality than anyother multiple-access protocols.

CI is distinguishable from conventional multicarrier modulation (MCM)techniques because it achieves both frequency diversity and bandwidthefficiency. CI is distinguishable from OFDM in that CI orthogonalizesdata symbols via interferometry in the frequency domain whereas OFDMmerely separates data symbols onto non-interfering frequencies. CIdiffers from MC-CDMA in that polyphase CI codes replace Hadamard-Walshor Gold codes typically used with MC-CDMA. This provides significantdifferences between signal and operational characteristics of CI-basedand MC-CDMA systems. For example, in MC-CDMA, CI codes are capable ofdoubling network capacity with almost no performance degradation.Furthermore, CI signals are substantially insensitive to phase jitterand frequency offsets, which are recognized as the major disadvantage ofconventional MCM.

CI codes may be employed in direct-sequence-like coding. Additionally,CI codes may be used for channel coding. CI codes and/or CI-basedsignaling may be used to encode data bits and/or data symbols. CI codingand CI-based codes may include interleaving.

CI enables the application of a redundantly modulated multicarrierarchitecture to conventional transmission protocols, such as TDMA,DS-CDMA, MC-CDMA, and OFDM. Specifically, CI carrier signals combine togenerate a superposition signal having time-domain characteristics thatcan be controlled via selection of the CI carrier characteristics (suchas phase, frequency, and amplitude). This enables CI to be compatiblewith legacy systems that use TDMA, DS-CDMA, pulse radio, etc. CI alsoimproves existing multicarrier protocols (such as OFDM and MC-CDMA).Thus, CI creates a common multicarrier architecture for all conventionaltransmission protocols.

The application of CI to DSSS and DS-CDMA is referred to as CI/DS-CDMA.

At the transmit side, the usual sinc and raised cosine pulse shapes usedwith DS-CDMA are replaced by a CI signal. For example, a DS-CDMAchip-shaping filter at a code generator is replaced with a chip-shapingfilter matched to the CI signal. At the receive side, a RAKE receiver ina typical DS-CDMA receiver is replaced by a receiver that performsfrequency decomposition and recombining. Each chip is separated into itsN frequency components and recombined in a manner that provides (1)optimal frequency-diversity benefits, (2) minimal inter-chipinterference, and (3) a reduction in additive noise power. Possiblecombining techniques include equal-gain combining (EGC), orthogonalrestoring combining (ORC), and minimum mean squared error combining(MMSEC). Upon recombining the chips, DS-CDMA spreading codes may beapplied to separate data symbols and/or data streams from each other.Variations to these transmit and receive side processing techniques, aswell as other types of processing, are described in the preferredembodiments.

Although the time-domain characteristics of CI/DS-CDMA signals aresimilar to DSSS and DS-CDMA signals (thus, making them compatible withconventional DS-CDMA networks), CI/DS-CDMA signals differ from DSSS andDS-CDMA signals. Instead of spreading information symbols over codechips (i.e., the time domain), CI spreads information symbols overinterfering subcarriers (i.e., the frequency domain). Consequently, thefrequency-domain characteristics of transmitted CI/DS-CDMA signals arefundamentally different than the frequency-domain characteristics ofDSSS and DS-CDMA signals. Furthermore, received CI/DS-CDMA signals areprocessed in the frequency domain (e.g., via frequency decomposition andcombining), whereas received DSSS and DS-CDMA signals are processed inthe time domain (e.g., via RAKE receivers).

Frequency-domain selectivity enables independent provisioning of CIsub-carrier channels to users who may only need a fraction of thebandwidth of a communication channel. In optical-fiber systems, a CIsignal is composed of multiple narrowband subcarriers that are lesssensitive to channel impairments, such as delay mode distortion. Thus,CI eliminates the need for high-speed equalization. This significantlyreduces transceiver complexity and can increase the range of opticalcommunication systems. The CI signal architecture, as well as efficientmodulation (e.g., phase-shift modulation, polarization-shift modulation)achieves higher data rates with lower-frequency optoelectronics.

The frequency profile of a CI superposition signal can be controlled byadjusting weights of CI carriers and/or selecting CI carrierfrequencies. This enables conventional single-carrier protocols, such asTDMA and DS-CDMA, to be implemented with a CI carrier architecturedistributed across non-continuous frequency bands. CI is alsocomplementary to SONET and wavelength-division multiplexing in opticalfiber.

Carrier-weight adjustment facilitates adaptation to multipath andjamming environments. Carrier weights may be used by either or both atransmitter and a receiver to compensate for fading and/or other formsof signal degradation, avoid deep fades and/or interference, and/oroptimize transmission power efficiency. A CI signal may be frequencyhopped to avoid interference and/or fading. Frequency hopping may beemployed to enhance security or frequency diversity.

CI allows network providers to deliver signals that are data rate andprotocol independent. This allows rapid, independent provisioning ofsub-carrier channels. Scalability is provided by adding CI sub-carriers,thus allowing a “pay as you grow” approach. Additionally, only onenetwork element needs to be provisioned in order to reconfigure thenetwork.

Frequency-domain and time-domain adjustments of CI superposition signalsmay be employed to generate wavelets. This link between CI and waveletsenables a simple conversion between CI carrier selection and weightadjustment and wavelet scaling and shifting. CI also provides amulticarrier architecture for encoding, transmitting, and receivingwavelets.

It is an object of the present invention to provide all types ofcommunication signals with immunity to fading, inter-symbolinterference, and other forms of channel distortion.

An advantage of the present invention is that it provides a commonmulticarrier platform that can be designed for TDMA, DS-CDMA, MC-CDMA,pulse radio, and OFDM. This can be implemented as a software-definedradio system that uses simple algorithms combined with CI to selectdifferent multiple-access protocols.

An advantage of the present invention is that a radio communicationmethod is provided that is compatible with high-order digitalmodulations.

An advantage of the present invention is that a CDMA radio communicationmethod is provided that can be used with transceiver arrays.

An advantage of the present invention is that a CDMA radio communicationmethod is provided that is compatible with advanced array adaptationtechniques and thereby separates signals based on spatial diversity,frequency diversity, and combined spatial/spectral diversity.

CI signals enable antenna arrays to achieve directionality and spatialdiversity simultaneously. This reduces the cost of antennainfrastructure deployment and improves system performance. Thus, theinvention allows concentration of complex operations at base stations inpoint-to-multipoint communication links, greatly reducing the cost ofthe overall system.

An advantage of the present invention is that a radio communicationmethod is provided that has space division multiple access, interferenceexcision, and channel equalization capability.

An advantage of the invention is that it increases throughput ofwireless and guided-wave communications. CI-based protocols are highlybandwidth efficient, allowing higher data throughput in a given amountof spectrum than any other transmission protocol. CI provides higherdata rates and supports more users than any other transmission protocol.

An advantage of the invention is that it enables improved signalquality. CI signals are highly resistant to interference and distortion.

An advantage of the invention is that it greatly reduces transmit powerrequirements. Received CI signals can be combined to use all of thetransmitted signal energy that gets reflected on the way to thereceiver. Other technologies make little or no use of reflected energy.

Some of the many wireless applications of the invention includelocal-area networks, cellular communications, personal communicationsystems, broadband wireless services, data link, voice radio, satellitelinks, tagging and identification, wireless optical links, campus-areacommunications, wide-area networks, last-mile communication links, andbroadcast systems. The invention may be used in non-wirelesscommunication systems, such as guided wave, cable, wire, twisted pair,optical fiber, and any networks connected via conducting elements.

Various aspects of the invention are applicable to many types of signalprocessing. Some of these types of processing include, but are notlimited to, transducer-array processing, space-time processing,space-frequency processing, interferometry, filtering, waveletprocessing, transform operations, frequency conversion, diversityprocessing, correlation, channel coding, error-correction coding,multiple-access coding, spread-spectrum coding, channel compensation,correlation, transmission-protocol conversion, and security coding andauthentication. Other applications and embodiments of the invention areapparent from the description of preferred embodiments and the claimsthat follow.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A illustrates CI carriers having phase fronts that are aligned ata specific time. The CI carriers combine to generate a plurality ofsuperposition signals that are orthogonal to each other in time.

FIG. 1B illustrates an in-phase superposition of CI carriers of acarrier set that produces a superposition signal corresponding to a sumof the superposition signals shown in FIG. 1A

FIG. 1C illustrates two sets of orthogonal superposition signals. Thesignals in each set are orthogonal to each other. However, signals in afirst set are quasi-orthogonal to signals in a second set.

FIG. 1D shows a summation of two orthogonal sets of CI signals whereinsignals in a first set are quasi-orthogonal to signals in a second set.

FIG. 2A shows a plurality of carrier signals defined by a range ofcarrier frequencies and sets of phase offsets, such as phase offsetsresulting in a particular time-domain characteristic of a superpositionof the carriers.

FIG. 2B shows a plurality of carrier signals defined by a range ofcarrier frequencies, sets of phase offsets, and sets of carrieramplitudes and a superposition of the carriers. Either or both thesuperposition signal and the set of carriers may be processed fortransmission and/or reception.

FIG. 3 shows a plurality N of carrier signals that are redundantlymodulated with a stream of data symbols s_(k)(t) associated with ak^(th) channel.

FIG. 4A illustrates the use of different phases and time intervalsapplied to one set of carrier frequencies to distinguish a k^(th)channel.

FIG. 4B represents a plurality of data symbols s₁(t), s₂(t), and s₃(t)modulated onto the same carrier frequencies within the same timeinterval.

FIG. 5 illustrates a plurality of time-offset carrier signals havingdifferent initial time offsets t^(o) _(kn).

FIG. 6A shows a plurality of carriers corresponding to a plurality M ofsubchannels each having a plurality N of carriers.

FIG. 6B illustrates a superposition of three subchannels that occupy thesame time-domain space.

FIG. 7 illustrates a time-offset code used with carrier-definedsubchannels.

FIG. 8 shows a plurality N of carrier frequencies wherein each carrierfrequency ƒ_(n) (n=1, . . . , N) has a plurality of phased subcarriers.

FIG. 9A shows a plurality N of incrementally spaced-in-frequency carriersignals that may be used as an underlying architecture for transmissionprotocols. Users and/or data channels having symbols that areredundantly modulated on all N carriers can be provided with Northogonal phase spaces.

FIG. 9B shows an arrangement of N incrementally spaced-in-frequencycarrier signals divided into M sets of carrier signals. Each set mayinclude one or more users and/or data channels. Each set may or may notinclude a similar number of carriers. The carriers in each set may beincrementally spaced or non-incrementally spaced.

FIG. 10A shows a single carrier frequency ƒ_(n) having multiplequasi-orthogonal phases φ_((mn)k) that can be used in a quasi-orthogonalphase-space division multiplexing technique.

FIG. 10B shows a plurality of carrier frequencies wherein each frequencyincludes multiple quasi-orthogonal phases.

FIG. 11 shows a CI-OFDM signal architecture for a plurality M of userswherein each user is provided with a unique set of carriers.

FIG. 12 shows a CI/MC-CDMA architecture in which a k^(th) user having ak^(th) phase space φ_(kn) is provided with a spreading sequence c_(kn)assigned to each of a plurality N of carriers. The spreading sequencec_(kn) may include binary or polyphase values.

FIG. 13A shows a time-domain representation of a plurality K of DS-CDMAcodes generated from a CI architecture. Each chip of each CI/DS-CDMAcode is generated from a CI superposition of carriers. Each chip isprovided with a binary code value corresponding to a DS-CDMA code.

FIG. 13B illustrates chip overlap, which can increase bandwidthefficiency and/or provide additional redundancy. Chip overlap introducesa quasi-orthogonal condition. In the example shown, chip overlap doublesthe code length without increasing bandwidth.

FIG. 13C shows one of many possible carrier architectures for aCI/DS-CDMA system.

FIG. 14A shows an embodiment of a CI/DS-CDMA transmitter.

FIG. 14B shows another embodiment of a CI/DS-CDMA transmitter.

FIG. 15A illustrates a plurality of orthogonal phase spacescorresponding to a plurality of CI carrier frequencies.

FIG. 15B shows a matrix of phase-shifted symbol values corresponding tocarrier frequencies (rows) and phase spaces (columns).

FIG. 16A illustrates at least some of the principle components of a CItransmission system.

FIG. 16B illustrates another embodiment of a CI transmitter.

FIG. 16C illustrates an alternative embodiment of a CI transmitter.

FIG. 16D illustrates basic components of a particular set of embodimentsof a CI transmitter.

FIG. 16E illustrates generalized components of a broad class of CItransmitters.

FIG. 16F illustrates basic components of a CI transmitter that impressesat least one data sequence, at least one channel code, and at least onemultiple-access code onto a plurality of carriers.

FIG. 17A illustrates how a CI/DS-CDMA signal can be characterized byboth time-domain and frequency-domain codes. CI may be characterized bymulti-dimensional codes with respect to other combinations of diversityparameters.

FIG. 17B illustrates a multi-dimensional signal with CI coding.

FIG. 17C illustrates a three-dimensional diversity-parameter space thatcan be modulated or impressed with CI codes.

FIG. 18A is a functional representation of one set of embodiments of aCI receiver.

FIG. 18B is a general illustration of a CI receiver, such as aCI/DS-CDMA receiver.

FIG. 18C illustrates one possible set of embodiments of a CI receiver.

FIG. 19A illustrates an embodiment of a CI receiver array.

FIG. 19B illustrates an alternative embodiment of a CI receiver array.

FIG. 19C illustrates an embodiment of the combiner shown in FIG. 19A.

FIG. 19D illustrates an embodiment of the combiner shown in FIG. 19B.

FIG. 20 illustrates a system adapted to transmit CI subspace coded datasymbols into a multipath channel and a receiver adapted to process anddecode the CI subspace coded data symbols.

FIG. 21A illustrates an embodiment of a space-time matched-filterreceiver of the present invention.

FIG. 21B illustrates an embodiment of a space-frequency matched-filterreceiver of the present invention.

FIG. 21C illustrates a space-time receiver of the present invention.

FIG. 21D illustrates a space-frequency receiver of the presentinvention.

FIG. 21E shows a generalized illustration of a multi-element receiver ofthe present invention.

FIG. 21F shows a multi-element receiver of the present invention.

FIG. 21G is a functional illustration of a multi-element receiver of thepresent invention.

FIG. 22 illustrates an array-processor receiver of the invention thatcombines space-time processing with space coding.

FIG. 23A illustrates one of many possible CI/DS-CDMA signal structurescorresponding to a set of apparatus and method embodiments of theinvention.

FIG. 23B illustrates signal structures of one set of embodiments of amulti-dimensional CI/DS-CDMA method and apparatus of the invention.

FIG. 24 illustrates a signal structure derived from an alternate set ofapparatus and method embodiments of the invention.

FIG. 25A illustrates a subspace processing method of the presentinvention.

FIG. 25B illustrates an alternative subspace processing method of thepresent invention.

FIG. 26A shows a frequency-versus-magnitude plot of an alternativeCI-based protocol.

FIG. 26B shows a frequency-versus-magnitude plot of an associatedconventional protocol.

FIG. 27 is a frequency-domain illustration of carrier placements formultiple CI channels. These carrier placements allow the CI channels tobenefit from frequency diversity of nearly the entire frequency band.

FIG. 28A illustrates a set of methods for generating CI-based signals.

FIG. 28B illustrates a set of methods for receiving one or more CI-basedsignals.

FIG. 29A shows a conventional 4×4 Hadamard-Walsh matrix that may be usedin the invention.

FIG. 29B shows a basic 4×4 CI matrix.

FIG. 30A shows a 4×4 CI matrix multiplied by a first row of aHadamard-Walsh matrix.

FIG. 30B shows a 4×4 CI matrix multiplied by a second row of aHadamard-Walsh matrix.

FIG. 30C shows a 4×4 CI matrix multiplied by a third row of aHadamard-Walsh matrix.

FIG. 30D shows a 4×4 CI matrix multiplied by a fourth row of aHadamard-Walsh matrix.

FIG. 31A illustrates a selection of quaternary-phase vectors from thematrices shown in FIG. 30A and FIG. 30C.

FIG. 31B illustrates a selection of binary-phase vectors from thematrices shown in FIG. 30A and FIG. 30C.

FIG. 31C shows a 4×4 poly-phase code matrix.

FIG. 32A shows an 8×8 Hadamard-Walsh matrix HW_(8×8) generated from a4×4 Hadamard-Walsh matrix HW_(4×4) using the Hadamard-Walshmatrix-expansion technique.

FIG. 32B shows an 8×8 CI matrix PC4 _(8×8) generated from the 4×4polyphase CI matrix shown in FIG. 31C via Hadamard Walsh matrixexpansion.

FIG. 32C shows an 8×8 CI matrix CI_(8×8) generated from a 4×4 CI matrixCI_(4×4) via Hadamard Walsh matrix expansion.

FIG. 33A shows an 8×8 CI matrix HW_(8×8)(1)×CI_(8×8) resulting frommultiplication of the 8×8 CI matrix CI_(8×8) shown in FIG. 32C by thefirst row vector HW_(8×8)(1) of the 8×8 Hadamard-Walsh matrix shown inFIG. 32A.

FIG. 33B shows an 8×8 CI matrix HW_(8×8)(2)×CI_(8×8) resulting from amultiplication of an 8×8 CI matrix CI_(8×8) by the second row vectorHW_(8×8)(2) in an 8×8 Hadamard-Walsh matrix shown in FIG. 32A.

FIG. 33C shows an 8×8 CI matrix HW_(8×8)(3)×CI_(8×8) resulting from amultiplication of the 8×8 CI matrix CI_(8×8) by the third rowHW_(8×8)(3) of the 8×8 Hadamard-Walsh matrix shown in FIG. 32A.

FIG. 33D shows an 8×8 CI matrix HW_(8×8)(4)×CI_(8×8) resulting from amultiplication of the 8×8 CI matrix CI_(8×8) by the fourth rowHW_(8×8)(4) of the 8×8 Hadamard-Walsh matrix, HW_(8×8).

FIG. 33E shows an 8×8 CI matrix HW_(8×8)(5)×CI_(8×8) resulting from amultiplication of the 8×8 CI matrix CI_(8×8) by the fifth row vectorHW_(8×8)(5) of the 8×8 Hadamard-Walsh matrix, HW_(8×8).

FIG. 33F shows an 8×8 CI matrix HW_(8×8)(6)×CI_(8×8) resulting from amultiplication of the 8×8 CI matrix CI_(8×8) by the sixth rowHW_(8×8)(6) in the 8×8 Hadamard-Walsh matrix, HW_(8×8).

FIG. 33G shows an 8×8 CI matrix HW_(8×8)(7)×CI_(8×8) resulting from amultiplication of the 8×8 CI matrix CI_(8×8) by the seventh row vectorHW_(8×8)(7) of the 8×8 Hadamard-Walsh matrix, HW_(8×8).

FIG. 33H shows an 8×8 CI matrix HW_(8×8)(8)×CI_(8×8) resulting from amultiplication of the 8×8 CI matrix CI_(8×8) by the eighth rowHW_(8×8)(8) in the 8×8 Hadamard-Walsh matrix, HW_(8×8).

FIG. 34A shows a set 16 octonary codes C(n) generated from multiplyingan 8×8 CI matrix CI_(8×8) by rows HW_(8×8)(n) of the 8×8 Hadamard-Walshmatrix HW_(8×8).

FIG. 34B shows auto correlations and cross correlations of the 16octonary codes C(n) shown in FIG. 34A.

FIG. 35 illustrates a decoding method of the invention in which datatransmitted on two codes may be processed with a single despreadingcode.

FIG. 36A shows a frequency-domain plot of a data symbol that isconverted to a wideband spread-spectrum signal via direct-sequenceprocessing.

FIG. 36B shows a frequency-domain plot of the data symbol shown in FIG.36A that is converted to a CI signal having a plurality N of narrowbandcomponents.

FIG. 37 shows a time-domain plot of a plurality N of narrowband CIcomponents and a data symbol, which can be represented by asuperposition of the CI components.

FIG. 38 illustrates frequency-domain characteristics of a typicaldirect-sequence signal 3801 in comparison to frequency-domaincharacteristics of a plurality of different CI/DS-CDMA signal types.

FIG. 39A illustrates a CI code mapped into a plurality of orthogonaldiversity-parameter values.

FIG. 39B illustrates a CI code mapped into a plurality of orthogonaltime slots.

FIG. 39C illustrates a CI code mapped into a set of orthogonalfrequencies.

FIG. 39D illustrates a plurality of CI code chips impressed onto aplurality of spatial directions.

FIG. 39E illustrates CI coding used with a transmitter array such thateach code chip corresponding to a multiple-access channel or channelcode is applied to an individual spatially separated transmitterelement.

FIG. 39F illustrates CI coding applied to a plurality of linearpolarized signals.

FIG. 39G illustrates CI coding applied to a plurality of circular (orelliptical) polarized signals having different precession rates.

FIG. 40A illustrates basic components of a CI transceiver.

FIG. 40B illustrates basic components of a CI-code generator

FIG. 41A illustrates general steps of a transmitting method of thepresent invention.

FIG. 41B illustrates general steps of a receiving method that may beperformed in conjunction with the transmitting method illustrated inFIG. 41A.

FIG. 42 shows basic components of a CI transceiver.

FIG. 43A shows a (2,1) polyphase (M-ary) convolutional encoder withconstraint length K=3.

FIG. 43B illustrates an M-ary trellis diagram that represents thefunction of the polyphase convolutional encoder shown in FIG. 43A.

FIG. 43C illustrates polyphase channel coding that may be provided by aCI channel coder coupled to a modulator adapted to perform M-arymodulation.

FIG. 43D illustrates a CI Trellis decoding technique that may be used todecode CI-coded signals.

FIG. 44A shows an embodiment of a CI coder that includes at least oneblock coder and at least one convolutional coder.

FIG. 44B shows an alternative embodiment of a CI coder that includes atleast one block coder and at least one convolutional coder.

FIG. 45A shows a decoder corresponding to the coder shown in FIG. 44A.

FIG. 45B shows a decoder corresponding to the coder shown in FIG. 44B.

FIG. 46 illustrates basic components of a turbo coder/decoder systemthat may be used to process CI codes.

FIG. 47A illustrates a set of data symbols and a plurality of CI pulsesthat are adapted with respect to a plurality of data symbols.

FIG. 47B illustrates a modulated CI pulse stream generated by impressingdata symbols onto a CI pulse stream.

FIG. 47C illustrates CI carrier components of the modulated CI pulsestream shown in FIG. 47B.

FIG. 48 shows a CI encoding system coupled to a transmitter and a CIdecoding system coupled to a receiver.

FIG. 49 illustrates relationships between basic CI symbol values w_(n)and data symbols s_(n) processed with CI code chips to produce the CIsymbol values w_(n).

FIG. 50 shows a block diagram of basic components used in a CI codingsystem and a CI decoding system.

FIG. 51 illustrates channel-code chips c_(nk) used to map a data symbold_(m) to multiple carrier frequencies.

FIG. 52 illustrates an application of multi-level coding of the presentinvention.

FIG. 53 illustrates a multi-level coding method of the invention thatspreads a data symbol over multiple frequencies and time intervals.

FIG. 54A illustrates a method of sub-channel coding.

FIG. 54B shows a subchannel coding technique combined with time-domaincoding.

FIG. 55 shows an embodiment of a transmitter for combined channel codingand multiple access.

FIG. 56 illustrates a receiver associated with the transmitter shown inFIG. 55.

FIG. 57A shows a continuous frequency-domain profile of a single-carriersignal.

FIG. 57B represents a simplified time-domain profile of a widebanddigital signal.

FIG. 57C is a frequency-domain illustration of an inefficientdecomposition of the wideband signal into a plurality of narrowbandcomponents. The frequency spectra of the components do not overlap. Theroll-off factor of an analog filter's frequency response causes somereceived energy (and thus, information) to be lost.

FIG. 58A shows a decomposition of a single-carrier or multicarriersignal into N carrier-frequency components.

FIG. 58B shows a frequency-domain plot of the signal shown in FIG. 58A.

FIG. 58C shows a decomposition of the signal shown in FIG. 58A into N′carrier components where N′>N.

FIG. 58D shows a frequency-domain plot of the signal shown in FIG. 58C.

FIG. 58E illustrates a spectral profile selected for transmission orreception in a particular communication channel. Frequency rangescharacterized by interference, jamming, fading, and/or frequencyallocations to other systems, applications, and/or users can selectivelybe avoided.

FIG. 59A illustrates a method of generating CI carriers in atransmission system.

FIG. 59B illustrates a method of generating CI carriers in adecomposition process in a receiver.

FIG. 60A illustrates a CI receiver adapted to generate a plurality of CIcomponent signals from a received single-carrier signal.

FIG. 60B illustrates an alternative embodiment of a CI receiver adaptedto process single-carrier signals.

FIG. 61 illustrates a repeater adapted to convert a received signal intooverlapping, orthogonal CI sub-carrier components, process thecomponents, and recombine the processed components prior to transmittingthe combined components.

FIG. 62 illustrates a CI receiver coupled to an antenna array whereinthe receiver is adapted to process a received single-carrier signal as aplurality of CI components.

FIG. 63 illustrates a CI-based matched-filter receiver adapted toprocess a single-carrier signal as a plurality of CI components.

FIG. 64A illustrates a CI receiving method adapted to process asingle-carrier signal.

FIG. 64B illustrates basic steps of a CI reception method.

FIG. 64C illustrates basic steps performed by a CI receiver.

FIG. 65 illustrates how conventional radio-processing techniques can beconsolidated into simple CI transceiver processes.

FIG. 66 illustrates an embodiment of a CI-based software-defined radio.

FIG. 67 illustrates basic baseband-processing components of a CItransceiver.

FIG. 68 illustrates transmission methods 6810 and reception methods 6820of the present invention.

FIG. 69A illustrates how digital, text, and analog signals are formattedfor different information signals.

FIG. 69B illustrates a formatting step adapted to process receivedsignals into different information signals.

FIG. 70 shows three orthogonal waveforms separated in frequency byinteger multiples of a separation frequency.

FIG. 71A is a normalized complex-plane representation of samples of asignal having a particular signal frequency collected at a sampling ratethat equals, or is some sub-harmonic frequency of, the signal frequency.Each sample corresponds to an integer number of full rotations in thecomplex plane.

FIG. 71B is a normalized complex-plane representation that illustrates anon-zero progressive phase offset for each sample of a signal having anorthogonal signal frequency (represented by frequency ƒ_(n−1)) relativeto a sampling rate ƒ_(sample)=ƒ_(n). Each sample corresponds to lessthan a full rotation (i.e., ƒ_(n−1)/ƒ_(n) rotations) in the complexplane.

FIG. 71C is a normalized complex-plane representation that illustrates anon-zero progressive phase offset for each sample of a signal having anorthogonal signal frequency (represented by frequency ƒ_(n+1)) relativeto a sampling rate ƒ_(sample)=ƒ_(n). Each sample corresponds to agreater than full rotation (i.e., ƒ_(n+1)/ƒ_(n) rotations) in thecomplex plane.

FIG. 72 is a normalized complex-plane representation of samplescollected over a symbol interval. In this case, samples of a signalhaving a signal frequency ƒ_(signal) collected at a sampling rateƒ_(sample)≠ƒ_(signal), where ƒ_(sample) is orthogonal to ƒ_(signal),fill an integer number of full rotations in the normalized complexplane. The samples are uniformly spaced throughout the unit circle, andthus, cancel.

FIG. 73 illustrates in-phase and quadrature-phase samples collected at aparticular sampling rate.

FIG. 74A illustrates combined values of 110 CI samples for each of 400frequencies in intervals of one cycle per symbol period T_(s).

FIG. 74B illustrates the combined values of 110 CI samples for each of800 frequencies spaced at 0.05 cycles-per-period intervals and centeredat 10 cycles per symbol period.

FIG. 74C illustrates a plot of sums of samples collected at a particularsample frequency for a plurality of sampled signal frequencies.

FIG. 75 is a plot of sums of samples collected at a particular samplefrequency for a plurality of sampled signal frequencies.

FIG. 76A illustrates samples of a signal having a frequency ƒ_(n)sampled at a sample frequency ƒ_(sample)=ƒ_(n). The samples arerepresented as vectors in a normalized complex plane. Sinceƒ_(sample)=ƒ_(n), the vectors map onto the same position in the complexplane. Thus, the samples add constructively.

FIG. 76B shows a representation of samples mapped as vectors in anormalized complex plane. The sample frequency is ƒ_(sample)=ƒ_(n) andthe sampled signal's frequency is ƒ_(signal)=ƒ_(n+1). Since the sampleand signal frequencies are orthogonal to each other and the samples arecollected over a symbol interval T_(s)=1/ƒ_(s), the samples areuniformly distributed around a unit circle in the complex plane. Thesamples combine destructively to produce a zero value.

FIG. 76C shows samples mapped on a unit circle in a complex plane. Thesamples correspond to a sample frequency of ƒ_(sample)=ƒ_(n) and asampled signal frequency of ƒ_(signal)=ƒ_(n+1.5). The samples arecollected over a symbol interval T_(s)=1/ƒ_(s). Since the sample andsignal frequencies are not orthogonal, there is a non-uniformdistribution of samples over the unit circle. Some of the samplescombine constructively to produce a non-zero value.

FIG. 76D illustrates a plurality of samples mapped onto a unit circle ina normalized complex plane. The samples correspond to a sample frequencyof ƒ_(sample)=ƒ_(n) and a sampled signal frequency ofƒ_(signal)=ƒ_(n+2). The samples are collected over a symbol intervalT_(s)=1/ƒ_(s). Since the sample and signal frequencies are orthogonaland not harmonically related, the samples are distributed uniformlyaround the unit circle. When the samples are summed, they cancel.

FIG. 76E shows samples mapped on a unit circle in a complex plane. Thesamples correspond to a sample frequency of ƒ_(sample)=ƒ_(n) and asampled signal frequency of ƒ_(signal)=ƒ_(n+2.5). The samples arecollected over a symbol interval T_(s)=1/ƒ_(s). Since the sample andsignal frequencies are not orthogonal, there is a non-uniformdistribution of samples over the unit circle. The samples combine toproduce a non-zero value.

FIG. 77A is a functional diagram that illustrates apparatus and methodembodiments of a coherent CI sampler.

FIG. 77B shows an alternative functional diagram that illustratesapparatus and method embodiments of a coherent CI sampler.

FIG. 78A shows part of a coded CI waveform that may be processed using aCI sampling algorithm.

FIG. 78B shows a table that illustrates 10 transmitted data symbols andcorresponding non-normalized received signal values for each of 10 phasespaces.

FIG. 79A illustrates two periods of a step function constructed from asuperposition of odd-numbered sinusoids.

FIG. 79B illustrates a portion of a Fourier transform of the stepfunction shown in FIG. 79A.

FIG. 80A is a frequency-domain representation showing a first frequencycomponent of a sampling step function that equals a desired carrierfrequency. A plurality of orthogonal frequencies is also shown that maycorrespond to undesired carrier frequencies. A second frequencycomponent of the step function is also shown. The second frequencycorresponds to a harmonic of the first frequency. If a carrier frequencyequals the second frequency, then the sampling step function generatesnon-zero values for both carrier frequencies.

FIG. 80B is a frequency-domain profile that shows a first plurality ofharmonics corresponding to both a first plurality of carriers and aplurality of components of a first sampling step function. Thefrequency-domain profile also shows a second plurality of harmonicscorresponding to both a second plurality of carriers and a plurality ofcomponents of a second sampling step function. The first and secondpluralities of carriers are orthogonal to each other. Thus, the firstsampling step function generates non-zero values for only the first setof carriers and the second sampling step function generates non-zerovalues for only the second set of carriers. Data symbols areadvantageously modulated onto more than one carrier of each carrier set.

FIG. 81 shows three sinusoidal waves having uniformly spaced frequenciesƒ₁, ƒ₂, and ƒ₃, and a step function 8111 having a frequency equal tofrequency ƒ₁.

FIG. 82 shows a step function having a particular phase and frequencyƒ_(n) superimposed over three sinusoidal waves having the same frequencyƒ_(n), but different phases.

FIG. 83 is a table that illustrates summed values of three frequencybins of a three-carrier signal generated for each of three desired phasespaces and for the two remaining undesired phase spaces.

FIG. 84 illustrates basic components of a CI-OFFT receiver.

FIG. 85 illustrates a plurality of five-level step functions havingorthogonal frequencies, which are shown over a partial symbol interval.

FIG. 86A illustrates a pulse resulting from a superposition of the stepfunctions shown in FIG. 85.

FIG. 86B illustrates a filtered superposition pulse generated bylow-pass filtering the pulse shown in FIG. 86A.

FIG. 87A illustrates a combined signal resulting from a superposition ofa plurality of step functions having a frequency offset ƒ₀.

FIG. 87B illustrates a low-pass filtered superposition signal in whichhigh-frequency components have been removed from the combined signalshown in FIG. 87A.

FIG. 88A illustrates a superposition pulse generated from a plurality ofbinary step functions.

FIG. 88B illustrates a filtered superposition pulse generated bylow-pass filtering the pulse shown in FIG. 88A.

FIG. 89A illustrates a functional embodiment of an inverse CI-OFFTsystem of the invention.

FIG. 89B illustrates an alternative functional embodiment of an inverseCI-OFFT system.

FIG. 89C illustrates yet another functional embodiment of an inverseCI-OFFT system.

FIG. 90 illustrates a wavelet constructed from a plurality of CIcarriers.

FIG. 91 illustrates a Morlet wavelet packet 9100 constructed from asuperposition of CI carriers.

FIG. 92A illustrates three overlapping CI pulses having differenteffective-carrier frequencies.

FIG. 92B illustrates a superposition signal produced by combining thethree CI pulses shown in FIG. 92A. The superposition signal ischaracterized by a uniformly changing frequency.

FIG. 92C illustrates a plurality of CI carriers that combine to generatethe superposition signal shown in FIG. 92B.

FIG. 93 illustrates a wavelet generated from a plurality of CI carriers.Signals may be expressed by wavelet parameters (τ_(n), s_(n)) and/or CIparameters (ƒ_(n), w_(n)). CI-based wavelets can be used to translatebetween wavelet parameters and CI parameters.

FIG. 94A illustrates a CI-based wavelet (i.e., a CI superpositionsignal) characterized by a high time resolution (i.e., a narrowtime-domain signal).

FIG. 94B illustrates a plurality of narrowband CI carriers that arecomponents of the superposition signal shown in FIG. 94B.

FIG. 94C is a frequency-domain illustration of the carriers shown inFIG. 94B. Each frequency-domain component is characterized by highfrequency resolution (i.e., a narrow frequency-domain signal).

FIG. 95A illustrates a portion of a particular signal having multiplefrequencies and transient signal characteristics. The signal may includean information signal. In some applications, the signal may be areceived signal that may include noise and/or distortion. In otherapplications, the signal may include a transmit data sequence.

FIG. 95B illustrates a plurality of narrowband CI signals that may becorrelated (or similarly processed) with an information signal toprovide a plurality of correlation values. The information signal may beprocessed, such as by filtering, to produce the correlation values. Thecorrelation values are indicative of carrier weights. The carrierweights, when applied to hypothetical narrowband CI signals (such asshown in FIG. 95B), provide a superposition signal with time andfrequency-domain characteristics of the information signal.

FIG. 95C illustrates a narrow time-domain signal resulting from asuperposition of the CI signals. The narrow time-domain signalrepresents a narrow time-domain portion of the information signal thatcontributes to a sum of the correlation values represented by the CIsignals shown in FIG. 95B.

FIG. 96A illustrates one aspect of the invention in which waveletparameters (such as scale factors, translations, and/or wavelet type)are modulated or otherwise impressed onto CI signals for transmission.

FIG. 96B illustrates a method of transmitting wavelet parameters over acommunication channel wherein the wavelet parameters are converted to CIcarrier weights.

FIG. 96C illustrates a method of conveying wavelet parameters as aCI-based signal wherein the wavelet parameters are converted to CIwaveforms.

FIG. 97A illustrates a CI reception method of the invention.

FIG. 97B illustrates an alternative CI reception method.

FIG. 97C illustrates steps of a CI reception method.

FIG. 98 illustrates a CI transceiver of the invention. A receiver systemcouples a transmitted signal out of a communication channel. Atransmitter system couples an information-bearing transmit signal into acommunication channel.

FIG. 99 illustrates a control circuit that processes one or more systemrequirements and, optionally, one or more channel characteristics toadjust one or more CI parameters in a CI transceiver.

FIG. 100A illustrates a plurality of subscriber units in a networkhaving a plurality of access points. At least one of the subscriberunits is adapted to generate a pilot or known reference signal that isprocessed by the access points in a channel-estimation step.

FIG. 100B illustrates a plurality of access points adapted to transmitchannel-compensated signals to at least one subscriber unit.

FIG. 101 illustrates a plurality of access points connected to anetwork. A central processing unit enables the access points to worktogether to enhance diversity and/or provide sub-space processing.

FIG. 102 illustrates a network architecture in which a plurality ofsubscriber units are adapted to function as routers and/or repeaters.

FIG. 103A illustrates a CI transceiver adapted to perform routing.

FIG. 103B illustrates a CI transceiver adapted to perform routing.

FIG. 104

FIG. 111A illustrates a method of receiving, processing, andre-transmitting signals.

FIG. 111B illustrates a system adapted to receive, process, andre-transmit signals according to the method outlined in FIG. 111A.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

The description of the preferred embodiments assumes that the reader hasa familiarity with CI described in the following publications, which areincorporated by reference:

-   B. Natarajan, C. R. Nassar, S. Shattil, M. Michelini, “Application    of interferometry to MC-CDMA”, accepted for publication in IEEE    Transactions on Vehicular Technology.-   C. R Nassar, B. Natarajan, and S. Shattil, “Introduction of carrier    interference to spread spectrum multiple access,” IEEE Emerging    Technologies Symposium, Dallas, Tex., 12-13 Apr. 1999.-   B. Natarajan and C. R. Nassar, “Introducing novel FDD and FDM in    MC-CDMA to enhance performance,” IEEE Radio and Wireless Conference,    Denver, Colo., Sep. 10-13, 2000, pp. 29-32.-   Z. Wu, C. R. Nassar, A. Alagar, and S. Shattil, “Wireless    communication system architecture and physical layer design for    airport surface management,” 2000 IEEE Vehicular Technology    Conference, Boston, Mass., Sep. 24-28, 2000, pp. 1950-1955.-   S. Shattil, A. Alagar, Z. Wu and C. R. Nassar, “Wireless    communication system design for airport surface management—Part I:    Airport ramp measurements at 5.8 GHz,” 2000 IEEE International    Conference on Communications, Jun. 18-22, 2000, New Orleans, pp.    1552-1556.-   B. Natarajan, C. R. Nassar, and S. Shattil, “Carrier Interferometry    TDMA for future generation wireless—Part I: Performance,” accepted    for publication in IEEE Communications Letters.-   Z. Wu, C. R. Nassar, and S. Shattil, “Capacity enhanced DS-CDMA via    carrier interferometry chip shaping,” IEEE 3G Wireless Symposium,    May 30—Jun. 2, 2001, San Francisco, Calif.-   Z. Wu, C. R. Nassar, and S. Shattil, “Frequency diversity    performance enhancement in DS-CDMA via carrier interference pulse    shaping,” The 13^(th) Annual International Conference on Wireless    Communications, Calgary, Alberta, Canada, July 7-10, 2001.-   C. R. Nassar and Z. Wu, “High performance broadband DS-CDMA via    carrier interferometry chip shaping,” 2000 International Symposium    on Advanced Radio Technologies, Boulder, Colo., Sep. 6-8, 2000,    proceeding available online at    http://ntai.its.bldrdoc.gov/meetings/art/index.html.-   Z. Wu and C. R. Nassar, “MMSE frequency combining for CI/DS-CDMA,”    IEEE Radio and Wireless Conference, Denver, Colo., Sep. 10-13, 2000,    pp. 103-106.-   D. Wiegand, C. R. Nassar, and S. Shattil, “High Performance OFDM for    next generation wireless via the application of carrier    interferometry,” IEEE 3G Wireless Symposium, May 30—Jun. 2, 2001,    San Francisco, Calif.-   B. Natarajan, C. R. Nassar, and S. Shattil, “Exploiting frequency    diversity in TDMA through carrier interferometry,” Wireless 2000:    The 12^(th) Annual International Conference on Wireless    Communications, Calgary, Alberta, Canada, Jul. 10-12, 2000, pp.    469-476.-   B. Natarajan, C. R. Nassar, and S. Shattil, “Throughput enhancement    in TDMA through carrier interferometry pulse shaping,” 2000 IEEE    Vehicular Technology Conference, Boston, Mass., Sep. 24-28, 2000,    pp. 1799-1803.-   S. A. Zekevat, C. R. Nassar, and S. Shattil, “Smart antenna spatial    sweeping for combined directionality and transmit diversity,”    accepted for publication in Journal of Communication Networks    Special Issue on Adaptive Antennas for Wireless Communications.-   S. A. Zekevat, C. R. Nassar, and S. Shattil, “Combined    directionality and transmit diversity via smart antenna spatial    sweeping,” 38^(th) Annual Allerton Conference on Communications,    Control, and Computing, Champaign-Urbana, Ill., Oct. 4-6, 2000.-   S. Shattil and C. R. Nassar, “Array Control Systems For Multicarrier    Protocols Using a Frequency-Shifted Feedback Cavity” IEEE Radio and    Wireless Conference, Denver, Colo., Aug. 1-4, 1999.-   C. R. Nassar, et. al., MultiCarrier Technologies for Next Generation    Multiple Access, Kluwer Academic Publishers: 2001.

Applications of CI, array processing, spatial interferometry, andrelated systems and methods are cited in the following patents andpatent applications, which are hereby incorporated by reference:

U.S. Pat. No. 5,955,992

U.S. Pat. No. 6,008,760

U.S. Pat. No. 6,211,671

U.S. Pat. No. 6,331,837

PCT Appl. No. PCT/US99/02838

PCT Appl. No. PCT/US00/18113

U.S. patent application Ser. No. 09/347,182

U.S. patent application Ser. No. 09/472,300

U.S. patent application Ser. No. 09/433,196

U.S. patent application Ser. No. 09/393,431

U.S. patent application Ser. No. 09/718,851

U.S. patent application Ser. No. 09/703,202

U.S. patent application Ser. No. 10/034,386

U.S. patent application Ser. No. 10/078,774

U.S. Provisional Pat. Appl. No. 60/163,141

U.S. Provisional Pat. Appl. No. 60/219,482

U.S. provisional Pat. Appl. No. 60/259,433

U.S. provisional Pat. Appl. No. 60/286,850

DEFINITIONS

Various terms used in the descriptions of CI methods and systems aregenerally described in this section. The descriptions in this sectionare provided for illustrative purposes only, and is not limiting. Themeaning of these terms will be apparent to persons skilled in therelevant art(s) based on the entirety of the teachings provided herein.These terms may be discussed throughout the specification and the citedreferences with additional detail.

The term carrier signal, or carrier, when used herein, refers to atleast one electromagnetic wave having at least one characteristic thatmay be varied by modulation. Carriers may be referred to as subcarriers.Other wave phenomena, such as acoustic waves, may be used as carriers.Carrier signals may include any type of periodic signal. Carrier signalsmay include sinusoids, square waves, triangle waves, wavelets, and/orarbitrary waveforms. A carrier signal is capable of carrying informationvia modulation. A carrier signal may be modulated or unmodulated.Multicarrier signals may include multi-frequency signals, multi-spatialsignals, multi-directional signals, multi-polarization signals,multiple-code signals, multiple sub-space signals, multi-phase-spacesignals, time-domain (discreet-time) signals, and/or any other set ofelectromagnetic signals having different orthogonal or quasi-orthogonalvalues of at least one diversity parameter. A code sequence can beregarded as a carrier signal.

Channel compensation describes signal processing performed on at leastone received signal according to channel fluctuations. Channelcompensation may include blind adaptive techniques. Alternatively,channel compensation may employ at least one pilot or training signal toprobe the channel. Known signals can be used to compensate for variousmultipath effects (such as fading and/or inter-symbol interference),adapt to non-linear channel distortions (such as chromatic dispersion,four-wave mixing, mode dispersion, and other guided-wave distortions),and/or remove multi-user interference and/or jamming signals. Channelcompensation may employ a combination of adaptive and reference-signalprocessing. Channel compensation may include adaptive channelequalization. Preferably, channel compensation in a CI and/or arrayimplementation employs some type of combining.

Channel estimation describes any combination of blind adaptivetechniques and reference-signal processing to determine signaldistortion resulting from the effects of at least one communicationchannel. In one example, a pilot symbol is transmitted periodically froma remote transmitter. A local receiver exploits the known transmissiontime, frequency, polarization, and/or any other diversity-parametervalue of at least one pilot symbol to process the transmitted pilotsymbol and estimate the distortion caused by the channel environment. Onthe basis of an estimated value, distortion in the received data symbolsis compensated.

A combiner, as used herein, describes any system, device, and/oralgorithm adapted to combine a plurality of signals or symbol values. Acombiner may combine multiple carriers or signal values to generate asuperposition signal. A combiner may provide weights to carriers orsignal values to generate one or more superposition signals havingpredetermined characteristics, such as time domain, frequency domain,spatial domain, sub-space domain, and/or other physical characteristics.A combiner may compensate for noise, interference, and/or distortion.

Combining often involves generating weights based on channel estimates.The weights may be adapted relative to some performance measurement,such as probability of error, bit error rate (BER), signal-to-noiseratio (SNR), signal-to-noise-plus-interference ratio (SNIR), and/or anyother appropriate signal-quality parameter. Performance measurements mayinclude any combination of instantaneous and averaged performancemeasurements. Averaging may be performed over one or more diversityparameters. A combiner may perform combining in more than onediversity-parameter space. For example, MMSE combining may be performedin the frequency domain to generate a plurality of combined signals thatmay be processed via equal-gain combining in the time domain. Othertypes of combining, as well as combining in different dimensions may beperformed.

A correlator or matched-filter receiver is any device, system, oralgorithm, or combination thereof adapted to correlate at least oneinput signal with at least one reference signal. A correlator ormatched-filter receiver generates at least one signal indicative of thedegree of correlation between at least one input signal and at least onereference. In one set of embodiments, the degree of correlation isevaluated using some signal-processing technique (e.g., shift and sum,weight and sum, sample and sum) that depends on the reference. Inanother set of embodiments, the correlator multiplies (or performs someequivalent operation) reference and input signals and sums the productsover a predetermined time interval. Various techniques are available forcorrelating a received signal with a reference sequence, including thoseusing surface acoustic wave (SAW) correlators, tapped delay line (TDL)correlators, serial correlators, and others. A non-coherent digitalmatched filter may be employed, such as a matched filter having fourreal filter channels to perform four-phase quantization in the complexplane. A matched-filter receiver may separate the received signal intoreal and imaginary parts and correlate both real and imaginary parts fora plurality of chip sequences (e.g., in phase and quadrature phase chipsequences). A matched-filter receiver may combine the real and imaginarysignals into a unified signal data stream. For each received symbol, thereceiver may determine which of a plurality of phase sectors in whichthe phase angle lies.

A decoder, as used herein, describes any system, device, or algorithmcapable of decoding an encoded information (e.g., data) signal. Adecoder typically decodes an encoded signal with respect to one or morereference signals (e.g., codes, decode sequences, code keys, etc.).Decoding may take the form of a correlation process (as definedmathematically), matched filtering, or any kind of processing (e.g.,complementary processing) that extracts at least one desired informationsignal from the coded signal. Correlation, as used herein withoutspecifically conveying the mathematical process of correlation, is meantto convey any process of decoding a signal. In a preferred embodiment,decoding involves summing samples collected over a predeterminedinterval. In another embodiment, collected samples are phase shiftedwith respect to at least one code before being summed. In somemulticarrier systems, it is impractical to perform matched filtering orthe mathematical correlation process. Rather, data symbols are obtainedfrom the output bins of a Fourier transform process. Similarly, othertypes of transforms or inverse transforms may be performed to decodesignals.

A guard interval is a redundant signal period designed to reduceinter-symbol interference by cyclically repeating the signal waveform ofthe effective symbol period. The effective symbol length, the guardinterval length and the number of carrier waves may be determined on thebasis of either a fixed-reception mode or a mobile-reception mode. Theoptimal values of the guard interval length, the effective symbollength, and other transmission parameters may vary depending on the modeof reception.

An information signal, as used herein, describes one or more signalsthat convey some form of useful information via magnitude, phase,frequency, polarization, mode, direction, and/or some signal propertyderived therefrom. CI-based information signals may include any type ofcommunication signal, such as, but not limited to voice, data, and text.Information signals may include any of various types of remote-sensingsignals, such as radar signals, Lidar signals, spectroscopy signals ofvarious types (e.g., absorption, scatter, luminescence, resonant,emission, harmonic, intermodulation, etc.), probing signals, and imagingsignals (e.g., X-ray, gamma-ray, ultrasound, seismic survey, acoustic,sonar, optical, pulse radio, spread spectrum, etc.). Any informationsignal may be considered to be a CI-based signal if it is processed viaCI signal-processing techniques. Thus, a received non-CI signal may beconverted into a CI signal by decomposing the received signal intoorthogonal sub-carrier components.

Interfering signals, as used herein, describes any plurality of signals(typically data symbols) impressed upon at least one similardiversity-parameter value. For example, two or more data symbols thatare impressed on the same frequency and time interval of a signalreceived by a receiver are interfering signals. Although, the receivermay be a multi-element receiver that can spatially discriminate between(or separate) the received data symbols, the data symbols are consideredto be interfering by virtue of the interferometry processing needed toseparate them.

The term modulation, as used herein, refers to at least one method ofimpressing some signal (such as an information signal, a code signal,and/or a sub-carrier) onto an electromagnetic signal. Modulationdescribes the adjustment of one or more physical signal characteristicswith respect to an information signal. Signals, such as analog and/ordigital information signals, may be impressed onto one or more carriersignals via any combination of modulation techniques, including, but notlimited to, amplitude modulation, phase modulation, frequencymodulation, pulse modulation, and/or polarization modulation. Pulsemodulation (such as CI-pulse modulation) may include pulse-amplitudemodulation, pulse-code modulation, pulse-frequency modulation,pulse-position modulation, and/or pulse-width modulation. CI methods arecommonly combined with modulation, such as Pulse Amplitude Modulation(PAM), Frequency Shift Keying (FSK), Phase Shift Keying (PSK), andQuadrature Amplitude Modulation (QAM). Coded modulation, such astrellis-code modulation, may be performed. Data symbols may be modulatedonto a code sequence, such as a multiple-access code, a spreading code,an encryption code, a channel code, etc. A code sequence may includedigital and/or analog signals. Examples of code sequences includedirect-sequence codes, MC-CDMA codes, CI codes, CI/DS-CDMA codes,frequency-hopping codes, chirp codes, coherence-multiplexing codes,sub-channel codes, and code length division multiplexing codes. Varioustypes of modulation can include the formation of code-chip values,continuous-code values, and/or code-chip sequences based on data-symbolvalues. Data symbols may be input to a code-generation process.

A multi-element receiver describes any receiver adapted to producemultiple separate signals relative to different diversity-parametervalues. Each element of a multi-element receiver preferably has adifferent responsiveness relative to at least one diversity parametervalue. For example, spatially separated receiver elements typically havedifferent amplitude and phase responses to received signals by virtue oftheir physical separation. This is particularly true when receivedsignals are affected by a multipath environment. A multi-elementreceiver may include a single reflector with multiple feeds.

A multi-element receiver may have a single interface to a communicationchannel but provide different responsiveness to signals having differentphysical characteristics. A receiver having a filter bank or equivalentfrequency-selective system can be regarded as a multi-element receiver.A receiver that processes a plurality of received coded signals is amulti-element receiver. A multi-element receiver may have selectiveresponsiveness relative to different values of one or more diversityparameters, such as, but not limited to, phase, mode, polarization,polarization-rotation rate, phase-rotation rate, frequencyrate-of-change, amplitude rate-of-change, angle of arrival, angle-ofarrival rate-of-change, spatial gain distribution, etc.

A multi-element transmitter, as recited herein, describes anytransmitter adapted to couple multiple interfering signals into acommunication channel. Interfering signals are signals having one ormore similar or overlapping diversity-parameter values or that result inhaving one or more similar or overlapping diversity-parameter values dueto propagation in a communication channel. A multi-element transmittermay include a single data source in which different data symbols ormultiple-access channels are transmitted on overlappingdiversity-parameter values.

A multi-element transmitter may include multiple data sources that areeach transmitted by a separate transmitter unit. A multi-elementtransmitter may include a multi-frequency transmitter, a multi-codetransmitter, a multi-polarization transmitter, a multi-directionaltransmitter, etc. Overlapping diversity parameters may include at leastone of mode, frequency, phase, amplitude, polarization,polarization-rotation rate, phase-rotation rate, angle of arrival,spatial location, spatial gain distribution, beam-pattern sweep rate,code, etc.

Orthogonal overlapping carriers describe two or more carriers that aremodulated such that their spectra overlap. If the frequency separationbetween any two adjacent frequencies is made equal to the reciprocal ofthe effective symbol period for multicarrier transmission, the nil pointof the frequency spectrum of each modulated wave coincides with thecenter frequency of the adjacent modulated waves. CI signals can includeorthogonal, overlapping signals. In some applications, CI carriers maybe orthogonal, whereas superpositions of the CI carriers may includepseudo-orthogonal time-domain waveforms.

A receiver, as used herein, includes any system, device, or process thatemploys any combination of detection and estimation. Detection is thetask of determining if a predetermined signal set is present in anobservation. Estimation is the task of obtaining or determining valuesof one or more signal parameters. A receiver may perform varioussignal-processing operations, including, but not limited to, filtering,channel selection automatic gain control, timing recovery, carrieracquisition, carrier recovery, bandwidth adjustment, sample-rateadjustment, matched filtering, soft-decision quantization,amplification, decoding, DC signal removal, equalization, combining,spectral shaping, noise-bandwidth control, spectral translation,amplifier linearization, de-interleaving, in-phase/quadrature-phase gainand phase balancing, etc.

A sub-space processor, as described herein, includes any system, device,or algorithm, or combination thereof capable of separating interferingsignals. Each separated interfering signal is said to occupy a signalsub-space. The type of signal sub-space corresponds to the type ofprocessing and/or the diversity parameter(s) that define theinterference. For example, a directional signal sub-space may correspondto phased array processing. A spatial signal sub-space may be defined asa subspace generated by spatial interferometry multiplexing. A phasesub-space (or phase space) can correspond to CI processing. Signalsub-spaces may be defined by one or more diversity parameters. Subspacesmay even have their own subspaces.

Synchronization describes one or more time-domain-related techniques bywhich various timing aspects of signal processing are controlled.Successful CI reception requires that a receiver maintain the correctsymbol synchronization and sampling frequency. Symbol synchronizationmeans that the receiver knows at which point of time each symbol beginsand times the symbol detection correspondingly. Sampling frequencyrefers to the frequency at which an A/D converter in the receiver takessamples from a received analog oscillation in order to convert thesignal into digital form.

Introduction to Carrier Interferometry

Various aspects of the present invention are based on CI. Other aspectsof the invention are particularly applicable to CI methods and systems.There are too many variations, permutations, and specificimplementations of CI to describe in this introduction. Accordingly, thedescriptions and examples of CI described herein are not intended tolimit the scope of how CI is defined, but rather to illustrate a few ofthe many ways that the present invention may be implemented.Descriptions of CI are also intended to clarify some of the aspects andembodiments of the present invention.

Inter-symbol interference occurs when a reflected signal travels adistance sufficiently greater than the distance traversed by aline-of-sight signal so as to cause a delay greater than the duration ofa data symbol. CI avoids inter-symbol interference by transmitting datasymbols on narrowband carriers. Multipath fading occurs when anarrowband signal traverses two paths having a half-cycle phasedifference. CI avoids the problem of multipath fading by transmittingeach data symbol on multiple carriers that are adequately separated withrespect to frequency (or some other diversity parameter). Redundantmodulation typically reduces bandwidth efficiency. CI avoids the problemof reduced bandwidth efficiency by modulating up to 2N data symbols oneach of N carriers. Increased interference on one or more carrierstypically increases probability of error. CI avoids the problem ofincreased interference and probability of error by exploitinginterferometry to orthogonalize data symbols modulated on the samecarriers. Thus, CI achieves higher throughput with better signal qualitythan any other multiple-access protocol.

FIG. 1A illustrates a basic form of CI in which a plurality of CIcarrier sets 105A, 105B, and 105C each have phase fronts aligned at aspecific time t₁, t₂, and t₃, respectively. A plurality of superpositionsignals 110A, 110B, and 110C result from a summation of each carrier set105A, 105B, and 105C, respectively. The superposition signal 110Aillustrates a pulse envelope centered at time t₁. All of the carriers105A are in-phase at time t₁ and thus, combine constructively. Thesuperposition signal 110A has a maximum magnitude at time t₁. At othertimes (e.g., times t₂ and t₃), the carriers in carrier set 105A combinedestructively, resulting in low or undetectable signal levels.

In CI, the individual signal components 105A, 105B, and 105Ccontributing to a CI pulse 110A, 110B, and 110C, respectively, orinformation symbol s_(n) have an extended duration T_(s) relative to thepulse width T_(pulse). The extended symbol duration T_(s) (i.e., theduration of component waveforms corresponding to a symbol s_(n)) reducesspectral sidelobes associated with the transmitted information symbols_(n). The extended waveform shape can be overlapped with extendedwaveforms associated with other symbols s_(n)′ (n′≠n). Naturally,interference will occur between the waveforms associated with differentdata symbols. However, CI coding can be employed to provideorthogonality (or quasi-orthogonality) between the composite waveforms(i.e., the data symbols s_(n)).

Although multicarrier-based CI signals (such as signals 110A, 110B, and110C) can resemble sinc-shaped pulses, which are orthogonalized bytime-domain pulse positioning, it is important to note thatmulticarrier-based CI signals are composed of multicarrier (e.g.,multi-frequency) components and are processed (e.g., generated and/ordecomposed) in the frequency domain.

The signal 110A results from an addition of N carriers that have auniform frequency separation ƒ_(s). FIG. 1A illustrates a simple case ofno tapered windowing of the carrier amplitudes. The CI carriers areuniformly spaced in frequency ƒ_(n)=ƒ₀+nƒ_(s), where f₀ is some zero ornon-zero offset frequency, ƒ_(s) is a non-zero shift frequency, and n issome integer or set of integers. A superposition CI signal, such assignal 110A, is expressed by:

${{e(t)} = {\sum\limits_{n = 1}^{N}^{t{\lbrack{{{({\omega_{c} + {n\omega}_{s}})}t} + {n\; {\Delta\varphi}}}\rbrack}}}},$

which has a magnitude of:

${{e(t)}} = {{\frac{\sin \left( {{N\left( {{\omega_{s}t} + {\Delta\varphi}} \right)}/2} \right)}{\sin \left( {\left( {{\omega_{s}t} + {\Delta\varphi}} \right)/2} \right)}}.}$

The CI signals are periodic with period 1/ƒ_(s) for an odd number ofcarriers N and with period 2/ƒ_(s) for an even number of carriers N. Themain lobe has a duration 2/Nf_(s) and each of the N−2 side lobes has aduration 1/Nf_(s). The amplitude of the l^(th) side lobe with respect tothe main lobe amplitude is:

${A(l)} = \frac{1}{N\; {\sin \left( {{\pi \left( {l + {1/2}} \right)}/N} \right)}}$

Applying a phase shift of nΔφ_(k) to each n^(th) carrier shifts the CIenvelope in time by Δt=Δφ_(k)/2πƒ_(s). Therefore, N signals can bepositioned orthogonally in time. The phase shifts can provide necessaryphase relationships to create the desired timing of the informationsignal received by at least one receiver (not shown).

The cross correlation between users is:

${{R_{cc}(\tau)} = {\frac{1}{2f_{s}}\frac{\sin \left( {N\; 2\pi \; f_{s}{\tau/2}} \right)}{\sin \left( {2\pi \; f_{s}{\tau/2}} \right)}{\cos \left( {\left( {N - 1} \right)2\pi \; f_{s}{\tau/2}} \right)}}},$

where τ the time shift between envelopes. Zeros occur at: k/Nf_(s), k=1,2, . . . , N−1 and at (2k−1)/2(N−1)f_(s), k=1, 2, . . . , N−1. CI cansupport N orthogonal users (or channels). If additional users or signalsneed to be accommodated, CI provides N−1 additional positions to placesignals.

A CI signal centered at time τ is orthogonal to the CI signal centeredat time t₁ whenever the difference between τ and t₁ is Δt=k/Nf_(s), k=1,2, . . . , N−1. This enables CI waveforms to represent informationsymbols located sequentially in time without creating inter-symbolinterference. The superposition signal 110D shown in FIG. 1B representsa sum of the orthogonally positioned superposition signals 110A, 110B,and 110C.

An offset in the time domain corresponds to linearly increasing phaseoffsets in the frequency domain. A CI signal with a time offsetτ=k/Nf_(s) is equivalent to a CI carrier set with carriers 1 to N havingphase offsets:

{φ₁,φ₂, . . . , φ_(N)}={0,2πk/N,2·2πk/N, . . . , (N−1)·2πk/N}.

Orthogonality between CI signals can be understood as an appropriatetime separation τε{k/ƒ_(s), k=1, 2, . . . , N−1} between superpositionsignals or as carriers of each carrier set coded with a differentpolyphase spreading sequence:

f(φ)={e ^(jθ1) ,e ^(jθ2) , . . . , e ^(jθN) }={e ^(j0) ,e ^(j2πk/N) , .. . , e ^(j(N−1)·2πk/N)}

with respect to values of k=0, 1, . . . , N−1.

A set of quasi-orthogonal signals can be determined from non-orthogonaltime offsets that minimize the mean-squared value of the interferencebetween the quasi-orthogonal signals. This criteria is satisfied bymultiples of a time-offset value Δt=1/(2Nf_(s)). FIG. 1C shows a firstset of N orthogonal signals 110D represented in time by:

{t ₁ ,t ₂ , . . . , t _(N−1)}={1/ƒ _(s),2/ƒ_(s), . . . , (N−1)//ƒ_(s)}.

A second set of N orthogonal signals 110D′ is represented in time by:

{t′ ₁ ,t′ ₂ , . . . , t′ _(N−1)}=1/(2/Nf _(s))+{1/ƒ_(s),2/ƒ_(s), . . . ,(N−1)//ƒ_(s)}.

The first set of signals 110D is quasi-orthogonal to the second set110D′ and results in a minimal amount of interference, as shown in FIG.1D.

This result can also be expressed in terms of carrier phase offsetsusing the equivalence between shifts in the time domain and phaseoffsets in the frequency domain. A first set of N orthogonal signals isrepresented in phase by N complex spreading codes:

ƒ₁(φ)={e ^(jφ1) ,e ^(jθ2) , . . . , e ^(jφN) }={e ^(j0) ,e ^(j2πk/N) , .. . , e ^(j(N−1)·2πk/N)}

A second set of N orthogonal signals is represented in phase by Ncomplex spreading codes:

ƒ₂(φ)={e ^(jφ′1) ,e ^(jφ′2) , . . . , e ^(jφN) }={e ^(j(0+Δφ)) ,e^(j(2πk/N+Δφ)) , . . . , e ^(j((N−1)·2πk/N+Δφ))}

where Δφ=π/N.

The superposition signal 110D in FIG. 1B can be thought of as asuperposition of complex-weighted carriers in a carrier set 105D or asum of the superposition signals 110A, 110B, and 110C. The carrier set105D represents a sum of the carrier sets 105A, 105B, and 105C. Thecomplex amplitudes of carrier set 105D can be characterized by acomplex-weight vector w=[w₁, w₂, . . . , w_(N)]. Each value w_(n) of theweight vector w corresponds to a particular carrier frequency ƒ_(n). Thevalues w_(n) can be derived from a complex addition of carriers in thecarrier sets 105A, 105B, and 105C. The values w_(n) can be derived fromsumming complex numbers representing the magnitude and phase of eachcarrier in the carrier sets 105A, 105B, and 105C.

CI signals demonstrate both excellent frequency resolution and excellenttime resolution. A CI signal is composed of multiple narrowband carriersthat allow it to be resolved into its frequency components. Whenobserved in the time domain, a basic CI signal is very narrow, enablingit to be easily separated from other CI signals and to resolve thechannel's multipath profiles.

Because the period and width of the pulse envelope depends on theamplitudes, relative phases, and frequency separation of the CIcarriers, the frequency of each carrier may be changed without affectingthe pulse envelope as long as the amplitudes, relative phases, andfrequency separation are preserved. Thus, frequency hopping andfrequency shifting of the carriers does not affect the temporalcharacteristics of the superposition signal, such as superpositionsignal 110A. Tapering the amplitude distribution of the CI carriersbroadens the main-lobe width and reduces the amplitude of the sidelobes.

A CI signal has a number of carrier signals that may each have abandwidth that is less than the coherence bandwidth of the communicationchannel. The coherence bandwidth is the bandwidth limit in whichcorrelated fading occurs. The total bandwidth of the CI signalpreferably exceeds the coherence bandwidth.

CI carriers corresponding to any particular user, channel, or datasymbol may be spaced in frequency by large amounts to achieve a largesystem bandwidth relative to the coherence bandwidth. In this case, CImakes use of frequency to achieve uncorrelated fading. However, anydiversity parameter or combination of diversity parameters may be usedto achieve uncorrelated fading over the system bandwidth, or evenbetween individual carriers.

The system bandwidth of a group of CI carriers may be selected relativeto the coherence bandwidth of one or more subchannels, such as spatialsubchannels. Carriers that are closely spaced in frequency may haveuncorrelated fading if they are transmitted from different locations orhave different degrees of directivity. CI carriers transmitted fromdifferent locations may have different fades over each spatialsub-channel and therefore, can benefit from diversity combining at areceiver (not shown).

Phase shifts applied to an n^(th) carrier to separate a k^(th) channelfrom adjacent channels are given by:

φ_(kn) =πknf _(s)(Δt)+φ^(o) _(kn) =πkn/N+φ ^(o) _(kn)

where φ^(o) _(kn) is an initial phase-offset corresponding to the n^(th)carrier and the k^(th) channel. The values of Δt depend on whether thechannel spacing is orthogonal or quasi-orthogonal.

Although FIG. 1A and FIG. 1B illustrate an in-phase superposition ofcarrier signals, this example can be extended to other superpositions ofCI. For example, the time offset Δt (and the corresponding carrier phaseshifts φ^(kn)) for adjacent channels may be applied to CIimplementations that do not have in-phase superpositions. The timeoffsets Δt (and thus, the phase shifts φ_(kn)) derived in this case arealso relevant to CI implementations that process the received carriersseparately. When each carrier is processed separately, phase-offsetcoding (in addition to the phase offsets φ_(kn) used to separatechannels) may be used to minimize the peak of the superposition signal.

The carrier sets 105A, 105B, and 105C have phase offsets correspondingto a pulse-width duration. However, any type of orthogonal (e.g.,non-overlapping) or quasi-orthogonal (e.g., overlapping) spacing may beprovided. Carrier sets having quasi-orthogonal (or non-orthogonal)spacing may be processed with multi-user (or multi-channel) detectiontechniques or with any other type of interference suppression.

FIG. 1A and FIG. 1B illustrate several levels of signal decompositionthat reduce a complex time-domain signal into simple components. Thetime-domain pulses may be scaled and positioned to produce apredetermined time-domain signal indicative of an information signal,coding, and at least one transmission protocol. Multiple frequencycomponents may be weighted to produce an information signal havingpredetermined time-domain characteristics. Similarly, multiple frequencycomponents that comprise the pulses may be selected and weighted toimpart predetermined characteristics to the pulses. The scale of thecomponents selected for signal processing can be selected to provide adesired granularity for the information architecture.

Modulation of the pulses, the carriers, or both may be performed overthe duration of the signals shown in FIG. 1A and FIG. 1B. Carriermodulation may be performed over a pulse-repetition period, a pulseduration, or any multiple or fraction of either.

FIG. 2A and FIG. 2B illustrate how a constant weight applied to each ofa plurality of carrier signals (e.g., carrier frequencies or time-offsetpulses) generates a periodic binary code (such as a DS-CDMA code)sequence. In this case, each CI pulse is represented by a pulseenvelope. A binary code chip β_(n)(k) applied to a pulse envelope isrepresented by an upright pulse (corresponding to β_(n)(k)=+1) or aninverted pulse (corresponding to β_(n)(k)=−1). CI pulses may include aneffective carrier signal bounded by a pulse envelope, as shown in FIGS.1A, 1B, 1C, and 1D. Polyphase code chips may be represented by phaseshifts of the effective carrier. Code chips may be impressed ontocarrier signals (e.g., carrier frequencies or time-offset pulses) viaany combination of modulation techniques, such as amplitude modulation,phase modulation, frequency modulation, pulse modulation, polarizationmodulation, etc. The code sequence may be modulated with informationsymbols over a code (pulse) period, or the information signal may beapplied to code weights applied to the carriers during a code interval.Information symbols may include M-ary modulated symbols.

Information modulation applied to each group of carriers may include arelative time offset corresponding to a constant phase offset φ⁰ _(kn).Modulation may include any modulation scheme including, but not limitedto, pulse-amplitude modulation, amplitude modulation includingcontinuous phase modulation (CPM) and phase shift key, phase modulationincluding continuous and shift key, frequency modulation includingcontinuous and shift key, time-offset modulation, and/or anydifferential modulation techniques. Modulated signals may include guardbands, cyclic prefixes, codes, and the like, which are well known in theart.

Known CPM signals include several variations; these include minimumshift keying (MSK) and its variations, e.g., Gaussian pre-filtered MSK(GMSK), superposed quadrature amplitude modulation (SQAM), and staggeredquadrature offset raised cosine modulation. Explanations of varioustypes of CPM techniques may be found in the following references: FrankAmoroso and James A. Kivett, “Simplified MSK Signaling Technique,” IEEETransactions on Communications, April 1977, pp. 433-441; Mark C. Austinand Ming U. Chang, “Quadrature Overlapped Raised-Cosine Modulation,”IEEE Transactions on Communications, Vol. Com-29, No. 3, March 1981, pp.237-249; Kazuaki Murota and Kenkichi Hirade, “GMSK Modulation forDigital Mobile Radio Telephony,” IEEE Transactions on Communications,Vol. Com-29, No. 7, July 1981, pp. 1044-1050; and J. S. Seo and K.Feher, “SQAM: A New Superposed QAM Modem Technique,” IEEE Transactionson Communications, Vol. Com-33, March 1985, pp. 296-300. The inventionmay utilize MSK signals. However, the use of other variants of MSK andother CPM signals are within the scope and spirit of the invention.

Various types of spread spectrum may be employed on each CI carrier. Forexample, direct-sequence coding, coherence multiplexing, code-lengthdivision multiple access, frequency-modulation sweep, and/or otherspread-spectrum techniques may be provided to each carrier.Spread-spectrum coding may be provided to prior to or followingmodulation.

FIG. 3 shows a plurality N of carrier signals that are redundantlymodulated with a stream of data symbols s_(k)(t) associated with ak^(th) channel. Each of the carriers may have a phase:φ_(kn)=φ_(kn)(t)+φ⁰ _(kn), where φ_(kn)(t) denotes a time-dependentphase and φ⁰ _(kn) denotes a constant-value initial phase. Thetime-dependent phase term φ_(kn)(t) can represent the relative phasevariation between a plurality of carrier signals resulting from thecarrier signals having different frequencies. The time-dependent phaseterm φ⁰ _(kn)(t) may include an impressed variation or coding to effectone or more benefits, such as reduced peak power of the superpositionsignal, enhanced security, improved diversity, and additionalmultiplexing/demultiplexing capabilities. The constant-valued terms φ⁰_(kn) may include zero and/or non-zero values. The terms φ⁰ _(kn) may beselected to provide operational benefits, such as reduced peak power ofthe superposition signal, coding, and enhanced channelization.

The terms φ_(kn) may be defined as parts of a code Φ_(k)=Φ(φ, t, k, n)that is a function of one or more elements of a set including phase φ,time t, channel (or user) k, and carrier n. Thus, a redundantlymodulated data stream s_(k)(t) can be represented as having been actedupon by the code Φ(φ, t, k, n). A received signal may include aplurality of data streams, each acted upon by various codes Φ(φ, t, k,n). A received signal can be defined as:

${R(t)} = {\sum\limits_{k = k^{\prime}}^{k^{''}}{\Phi_{k}{{s_{k}(t)}.}}}$

One possible method for processing a coded data stream includesproviding inverse coding to the received signal in order to decode atleast one desired data stream:

ŝ _(k)(t)=Φ_(n) ⁻¹ R(t).

Additional processing may be performed including, but not limited to,distortion compensation, multi-user detection, interferencecancellation, filtering, sampling, and/or additional decoding.

FIG. 4A illustrates different phases and time intervals applied to oneset of carrier frequencies to distinguish a k^(th) channel from at leastone other channel. The set of carriers includes a plurality N of carrierfrequencies that are redundantly modulated with a stream of data symbolss_(k)(t) associated with the k^(th) channel. However, each carrier ismodulated in at least one of a plurality of time intervals, and at leastsome of the symbols s_(k)(t) of the k^(th) data stream are spread acrossmultiple time intervals. This provides both frequency diversity and timediversity to the k^(th) channel.

FIG. 4B represents a plurality of data symbols s₁(t), s₂(t), and s₃(t)that are each modulated onto the same carrier frequencies within thesame time interval. Unlike conventional OFDM, which transmits one databit per frequency channel per time slot, CI provides orthogonality tomultiple data symbols sharing the same frequency channel and time slot.OFDM merely acts as a group of single-carrier channels, whereas in CI,the individual carriers work together to convey data symbols. Each ofthe CI carriers having an n^(th) frequency ƒ_(n) has a phase:

φ_(kn)=φ_(kn)(t)+φ⁰ _(kn),

where φ_(kn)(t) denotes a time-dependent phase and φ⁰ _(kn) denotes aconstant-value initial phase. In this case there are three channels, sok has values of 1, 2, and 3.

An n^(th) carrier frequency of a k^(th) channel may have a time offsett_(kn) where:

t _(kn) =t _(kn)(t)+t ⁰ _(kn).

The term t_(kn)(t) denotes a time-varying time offset (or interval starttime) and t⁰ _(kn) denotes a constant-value initial time offset. Thetime-varying term t_(kn)(t) may represent a plurality of time intervalsthat are uniformly spaced (e.g., t_(kn)(t)=mΔt_(kn), where m=0, 1, 2, .. . , and Δt_(kn) is some constant time interval) or non-uniformlyspaced. A k^(th) channel may be provided with a phase code Φ_(k) and/ora time code T_(k) wherein phase values φ_(kn) and/or time values t_(kn)are predetermined or adapted with respect to at least one performanceobjective, such as reducing peak power, improving asignal-to-interference plus noise ratio, enhancing diversity, providingsecurity, reducing a BER, etc.

FIG. 5 illustrates a plurality of time-offset carrier signals havingdifferent initial time offsets t⁰ _(kn). Data streams (or any other typeof information signal) may be redundantly modulated onto the time-offsetcarrier signals, either directly or with respect to some spreading codecorresponding to time-offsets, phase-offsets, carrier frequency, phase,or the like. The time intervals may have uniform or non-uniformduration. Each time interval typically has a duration of about a symbolinterval. However, the time intervals may have durations that are longeror shorter. The time intervals may overlap, adjoin each other, or theymay be separated.

One method for demultiplexing a k^(th) channel from a received signalincludes compensating for coded time offsets and/or phase offsets andthen processing the signal components separately. Each carrier may beprocessed separately by a matched filter and decision system. Anothermethod involves processing superpositions of the compensated components.The superpositions may be pre-processed with any well-known detectiontechnique, such as matched filtering, down-conversion, envelopedetection, Fourier transform, demodulation, decoding, etc. A preferredmethod for demultiplexing a k^(th) channel from a received signalincludes filtering the components of the coded signal and/or thesuperposition of the components.

FIG. 6A illustrates a plurality of carriers corresponding to a pluralityM of subchannels each having a plurality N of carriers. The carriersshown are uniformly spaced in frequency ƒ_(s). The total bandwidth ofthe channel is proportional to NMf_(s). The bandwidth of a subchannel isrelated to Nf_(s). However, the bandwidth of each subchannel may occupyfrequency-band portions distributed over a wide bandwidth (e.g., afrequency band approximately equal to NMf_(s)) or over multiplenon-contiguous bands.

FIG. 6B illustrates a superposition of three subchannels that occupy thesame time-domain space. However, the separability of the time-domainsignals into their frequency components provides orthogonality to thesignals (and the subchannels). FIG. 6A and FIG. 6B illustrate how awideband signal can be separated into smaller-bandwidth subchannels thatare easier to process in the time domain. The duration of each datasymbol in a subchannel is M times the duration that a data symbol wouldhave if its bandwidth occupied the total channel. However, eachsubchannel can be positioned such that the group of subchannels occupiesalmost the full bandwidth of the total channel. This enables a group ofsubchannels to derive substantially the same frequency-diversitybenefits of the total channel.

FIG. 7 illustrates how time offsets may be used simultaneously withcarrier-defined subchannels. Modulated carriers corresponding to eachsubchannel may be decoded relative to a time-spreading code andprocessed separately or combined to produce a superposition signal. Thesubchannels may employ other types of coding (such as phase coding) aswell. Phase decoding, as well as time-offset decoding, andcarrier-frequency selection may be performed to separate subchannels andfacilitate processing of the data streams modulated on the subchannels.

Subchannels s₁(t), s₂(t), and s_(M)(t) are shown having carriercomponents occurring in three different time intervals. An m^(th)communication channel may be determined by an m^(th) code sequence ofcarrier frequencies and time slots. For example, a symbol value forsubchannel s₁(t) is modulated onto the following carrier frequency-timeinterval pairs: ƒ₁:t₂, ƒ_(M+1):t₀, and j_((N−1)M+1):t₁. More than onesubchannel may use the same set of carrier frequencies and timeintervals if different phases are provided. Although FIG. 7 showsuniformly spaced frequencies and time slots, non-uniform spacing may beemployed.

A subchannel data stream encoded according to one or more of thetechniques described in the specification may be processed at a receiverusing one or more decoding techniques. A receiver may shift a pluralityof its carriers with respect to a decoding sequence corresponding to oneor more transmission channels. The decoded signals may be processedseparately or combined to create a superposition signal. Alternatively,the receiver may generate a reference signal based on the code(s) of oneor more channels and use the reference signal in a matched filter orequivalent receiver system to process the received signals.

A receiver, such as a CI receiver, may include one or more digitalsystems and/or algorithms, including, but not limited to, A/Dconverters, down converters, synthesizers, matched filters, filterbanks, loop filters for carrier and/or symbol tracking, resamplingfilters (e.g., variable bandwidth and variable data rate resamplingfilters), AGC control loops, DC cancellers, demodulators, soft-decisionquantizers, decoders, re-encoders, de-scramblers, de-interleavers, etc.

FIG. 8 shows a plurality N of carrier frequencies. A group ofsubcarriers is associated with each carrier frequency ƒ_(n) (n=1, . . ., N). Each subcarrier is distinguished by one of a plurality M of phasesφ_(mn). The subcarriers may be modulated and transmitted by a singletransmitter. In this case, multipath effects (which causefrequency-dependent amplitude and phase variations in the carrierfrequencies) do not affect the relative phases φ_(mn) and relativeamplitudes of same-frequency subcarriers in each group of subcarrierstransmitted by the single transmitter.

Groups of subcarriers transmitted by other transmitters may experiencetransmitter-specific multipath effects (such as due to correspondingpropagation environments, transmitter-impressed multipath and/or coding,and/or different receiver responses to signals transmitted by differenttransmitters). Transmitter-specific multipath effects may be exploitedby the invention to separate interfering groups of subcarriers. Forexample, spatial processing, beam forming, interferometry, or any othertype of appropriate diversity-parameter processing may be performed toseparate signals transmitted by a plurality of transmitters.

In a preferred embodiment of the invention, the carrier frequencies areorthogonal. Thus, the carrier frequencies are separable via varioussignal-separation techniques, such as filtering and correlation. Inanother preferred embodiment of the invention, the carrier frequenciesare non-orthogonal or quasi-orthogonal. Thus, data symbols modulatedonto different non-orthogonal carrier frequencies may be separable usingmulti-user or multi-channel detection between two or more carrierfrequencies.

One embodiment of the invention separates a plurality of data symbolsmodulated onto interfering subcarriers each having a similar carrierfrequency ƒ_(n). For example, filter banks or a plurality of matchedfilters may be used to provide differing proportions of interferingsignals to a multi-channel detector (e.g., a weight-and-sum canceller,matrix diagonalizer, or the like). In this case, the differentproportions correspond to different carrier phases φ_(mn). Otherdiversity parameters (as well as diversity parameter combinations) maybe employed to enable multiple access within a carrier-frequencychannel.

A multi-channel detector separates the interfering signals and thus,enables a system capacity that approaches N·M. This corresponds to abandwidth efficiency of M symbols/Hz. Spatial processing furtherenhances system capacity. If K spatial sub-channels are created, systemcapacity may be increased by a factor of K. If an L-arydifferential-modulation scheme is employed, system capacity andbandwidth efficiency may be multiplied by the value L. Maximum systemcapacity CS is expressed by:

C_(s)=N·M·K·L

and maximum bandwidth efficiency e_(BW) is expressed by:

e _(SW)=M·K·L.

Diversity may be exploited to provide capacity and/or signal-qualitybenefits. In some cases, such as in interference-limited spread-spectrumsystems, signal quality and system capacity can be improvedsimultaneously. Since multipath fading may cause certain frequenciesand/or spatial locations to be unusable, the maximum system capacityC_(s) and bandwidth efficiency e_(BW) may not always be attainable.Redundancy may be employed in one or more diversity spaces to optimizethe bit error rate. For example, multiple antennas may be used by thetransmitter and/or the receiver to provide spatial redundancy.Similarly, different carrier frequencies may be modulated with the samedata symbols.

Redundant modulation may be augmented with coding, such asmultiple-access codes used as channel coding to encode data symbols.These codes may include standard binary codes, such as long codes, Goldcodes, Hadamard-Walsh codes, etc. The codes may include CI codes ordirect-sequence coding derived from any transform operation.

In one embodiment of the invention, the carrier signals shown in FIG. 8may be redundantly modulated. The different-frequency carrierscorresponding to phases φ₁₁, φ₁₂, and φ₁₃ may be modulated with a firstdata symbol. Phases φ₂₁, φ₂₂, and φ₂₃ may be modulated with a seconddata symbol. Phases φ₃₁, φ₃₂, and φ₃₃ may be modulated with a third datasymbol. This redundancy allows a receiver to select a preferred resultfrom a set of three processes. Thus, fading or interference thatsubstantially degrades one or two of the carrier frequencies does notsubstantially affect the BER of the received symbols. In one embodiment,the effects of interference and signal distortion at one or more carrierfrequencies are distributed substantially evenly to all users such thatno user experiences complete debilitation of their channel. In anotherembodiment, carrier frequencies may be changed to avoid deep fadesand/or interference. Carrier-frequency selection and/or adjustment maybe performed as a means of power control.

An alternative method for processing the received signals includescorrelating the phase-frequency combinations for each data symbol andsumming the correlation signals. A data symbol may be modulated (orotherwise impressed) onto a single carrier phase φ_(mn) corresponding toan m^(th) phase in an n^(th) frequency. A k^(th) data symbol may bemodulated onto a k^(th) set of carrier phases (φ_(mn))_(k) correspondingto multiple m phases and multiple n frequencies. One or more of thecorrelation signals may be weighted with a complex weight, a vector ofcomplex weights, or a complex-weight matrix prior to summing.

Each sub-carrier phase within a carrier frequency may experienceinterference from at least one other sub-carrier phase. In one case, ak^(th) data symbol (or data channel) is redundantly modulated ontomultiple carrier frequencies with respect to a k^(th) group of phaseshifts (φ_(mn))_(k). Subsequent data symbols are redundantly modulatedonto the same set of frequencies. For example, a k^(th) data symbol (ordata channel) is redundantly modulated onto the same carrier frequencieswith respect to a different (k^(th) group) of phase shifts(φ_(mn))_(k′). The total interference (I_(k′k))_(T) between the k^(th)data symbol and the k^(th) data symbol is expressed by:

$\left( I_{k^{\prime}k} \right) = {\sum\limits_{n}{\left( I_{k^{\prime}k} \right)n}}$

where interference between the data symbols is summed over the n carrierfrequencies.

Since the interference (I_(k′k))_(n) depends on the relative phasedifference Δφ_(mn)=φ_(m′n)−φ_(mn) between the m^(th) and m′^(th) phasesfor an n^(th) carrier frequency, the phases φ_(mn) may be selected suchthat the sum of the interferences is zero or very small:

$\left( I_{k^{\prime}k} \right)_{T} = {{\sum\limits_{n}\left( I_{k^{\prime}k} \right)_{n}} = 0}$

In another embodiment of the invention, the interference terms may beweighted with complex weight values w_(mn) such that the sum of theinterferences is zero or very small:

$\left( I_{k^{\prime}k} \right)_{T} = {{\sum\limits_{n}{w_{mn}\left( I_{k^{\prime}k} \right)}_{n}} = 0}$

Each complex weight value w_(mn) may include a single complex value, avector of complex weights, or a matrix (or higher-order distribution) ofcomplex weights.

In FIG. 8, a superposition signal S_(k) corresponds to a k^(th) group ofphases (φ_(mn))_(k) for a special case in which m=k and the relativephases φ_(mn) within each n carrier are associated with incrementaltranslations (in time) of the carrier. Thus, carrier phases φ_(k1),φ_(k2), . . . . , φ_(kN) are redundantly modulated with a k^(th) symbols_(k)(t). In this case, there are three superposition signals S₁, S₂,and S₃ that are centered at times t₁, t₂, and t₃, respectively.

The phases φ_(1n) of the carrier frequencies ƒ_(n) that correspond tothe first symbol s₁(t) produce a maximum (i.e., a superposition peak) attime t₁. Similarly, the second symbol's s₂(t) phase relationships φ_(2n)provide for in-phase carriers at time t₂. The third phase relationshipsφ_(3n) provide in-phase constructive combining between carriers at timet₃. In this case, the superposition signals S₁, and S₃ do not overlapand, therefore, are substantially orthogonal in the time domain.Consequently, the phase relationships φ_(km) of the correspondingcomponent carriers ensure orthogonality between the redundantlymodulated symbols s_(k)(t).

The relative phase of each carrier corresponding to a k^(th) orthogonalsuperposition signal S_(k) is related to an integer multiple of thesuperposition-signal width:

φ_(mn)=(1/ƒ_(s) N)2πƒ_(n) m

where (1/ƒ_(s)N) expresses the width. The term ƒ_(s) is the frequencyseparation and N is the number of carrier frequencies. An n^(th) carrierfrequency is expressed by ƒ_(n).

The time orthogonality of superposition signals (such as thesuperposition signals S₁ and S₃) demonstrates one class of orthogonalityrequirements for phase relationships φ_(mn). However, the presentinvention may use orthogonal phase relationships that result insuperposition signals that are not orthogonal in the time domain. Forexample, phase offsets may be provided to each carrier, such as toreduce the peak-to-average power of each superposition signal.Furthermore, various carrier-frequency and/or carrier-amplitudedistributions may be used that support orthogonal or quasi-orthogonalphase spaces, but may not provide orthogonality in the time domain.

The use of pseudo-orthogonal coding is well known in spread spectrum andis equally applicable to CI. FIG. 8 also illustrates one form ofpseudo-orthogonal phase coding that is illustrated by pseudo-orthogonaltime-domain superpositions S₁, S₂, and S₃ of the carrier signals. Therelative phase of each carrier corresponding to a k^(th) superpositionsignal S_(k) is related to an integer multiple of half thesuperposition-signal width:

φ_(mn)=(1/ƒ_(s) N)πƒ_(n) m

Pseudo-orthogonal phase relationships employed by the present inventiondo not necessarily have a quasi-orthogonal corollary in the time domain.For example, phase offsets may be provided to each carrier, such as toreduce the peak-to-average power of the superposition signals. Variouscarrier-frequency and/or carrier-amplitude distributions may be usedthat support orthogonal and/or pseudo-orthogonal phase spaces. Thesedistributions may or may not be characterized by pseudo-orthogonality inthe time domain.

Several embodiments of the present invention use space-frequencyprocessing at either or both a transmitter and a receiver. Thisprocessing substantially eliminates inter-symbol interference caused bychannel correlations across space (antenna correlation) and time (delayspread). This processing may include one form of CI processing, whichdecomposes a wide-bandwidth, high data rate communication signal into aplurality of small-bandwidth, low data rate channels without changingthe time-domain characteristics of the wideband signal. For example,DS-CDMA may be decomposed into component signals at a transmitter andprocessed using advantageous parallel-processing and/ornarrowband-processing techniques. A CI DS-CDMA signal may be received bya receiver and processed in any of several ways. A received CI DS-CDMAsignal may be processed as a conventional DS-CDMA signal. A receivedsignal may be processed with respect to its narrowband components in anarray-processing operation or the like. A CI receiver may be used toprocess CI DS-CDMA components and exploit capacity and signal-qualitybenefits of CI.

FIG. 9A shows an arrangement of N incrementally spaced-in-frequencycarrier signals. This case illustrates one set of N carriers capable ofhaving up to N orthogonal phase spaces wherein each of the phase spacesspans the entire set of carriers. The symbol duration T_(s) is equal tothe inverse of the carrier-frequency spacing ƒ_(s). In a firstembodiment of a CI architecture, a single user may use all of theavailable phase spaces. In a second embodiment, a plurality of users mayuse the same set of carriers but be assigned to different phase spaces.

FIG. 9B shows an arrangement of N incrementally spaced-in-frequencycarrier signals divided into M sets of carrier signals. In this case,each of the M carrier sets includes N/M carriers. There are N/Morthogonal phase spaces per set of carriers. The symbol duration T_(s)is equal to the inverse of the carrier-frequency spacing ƒ_(s).Carrier-frequency spacing in each carrier set may be selected to reducecorrelated fading between adjacent carrier frequencies.

In a third embodiment of a CI architecture, each user is assigned to oneof the M carrier sets. In one case of this embodiment, multiple usersmay be assigned to the same carrier set. Each user sharing a particularcarrier set may be assigned to one time slot and/or phase space.Alternatively, each user sharing a carrier set may use more than on timeslot and/or phase space. In another case of the third embodiment, onlyone user is assigned to each carrier set and that user can use one ormore of the available phase spaces and/or time slots.

In a fourth embodiment of a CI architecture, each user is assigned to aplurality of the M carrier sets. In one case of the fourth embodiment,each user is assigned to the same constructive-interference time slot(or equivalent phase space) for each of the carrier sets to which theuser is assigned. In another case of the fourth embodiment, each user isassigned to a different time slot and/or phase space relative to eachcarrier set. In another case, each user is assigned to a plurality oftime slots and/or phase spaces for each carrier set. This plurality oftime slots and/or phase spaces may include similar or different timeslots and/or phase spaces relative to the different carrier sets.

In a fifth embodiment of a CI architecture, multiple users are assignedto the same time slot(s) and/or phase space(s) relative to each of oneor more carrier sets. In this case, a code is applied to each phasespace and/or superposition signal to differentiate users. For example,code chips applied to superposition pulses can provide a DS-CDMA signalin the time domain. In another example, the application of code chips tofrequencies that comprise a phase space can enable information symbolsmodulated in that phase space to be separable from other symbolsmodulated in that phase space with a different code.

One advantage of the class of CI architectures illustrated in FIG. 9B isthat it allows a multicarrier protocol consisting of N carriers to beseparated into smaller groups of carrier signals that are easier toprocess. The smaller groups also provide substantially the samefrequency-diversity benefits as the full N-carrier architecture. Thesize of these groups and the carrier frequencies employed by each groupmay be adapted with respect to system and environment factors, such asfading, distortion, and interference.

FIG. 10A shows a single carrier frequency ƒ_(n) having a set ofquasi-orthogonal phases φ_((mn)k) used in a quasi-orthogonal phase-spacedivision multiplexing technique. In this case, a k^(th) user is providedwith M phase channels. Alternatively, the phase channels may correspondto different users. The advantage of assigning all of the phase channelsfor a given frequency to a single transmitter is that each of the phasechannels undergoes the same multipath effects and interference in acommunication channel. Known correlations between the phase channels canbe used to help separate interfering symbols transmitted on thosechannels. However, interference and multipath distortion do notsubstantially affect correlations between the phase channels.

FIG. 10B shows a plurality of carrier frequencies ƒ_(n) to ƒ_(n′) havingsets of quasi-orthogonal phases φ_((mn)) to φ_((mn′)). In this case, thenumber M of phase spaces is greater than the number N of carrierfrequencies. Multiple carriers may be used to increase capacity ormitigate the effects of fading and interference via redundantmodulation. In one case, the phases of each carrier may be selected withrespect to incremental time offsets. In another case, the carrier phasesmay be incrementally spaced in phase. For example, binary phase-shiftkey modulation may be implemented with carrier phases spaced throughoutan interval of 0 to π. Quadrature shift-key modulation may beimplemented with carrier-phase channels throughout an interval of 0 toπ/2. Differential amplitude modulation may also be performed incarrier-phases channels.

Coding may be provided to distribute a data symbol over a plurality ofcarrier frequencies, time intervals, and/or phases. Such codingtechniques are commonly employed in OFDM. Similarly, guard bands, cyclicprefixes, and various signal-processing techniques used with OFDM andother multicarrier protocols may be provided to CI signals.

For M>N, multi-user detection is typically used to separate interferingdata symbols. A multi-user detector may sample multiple phase offsetsφ_(mn) for each carrier frequency. Sampling may be achieved via matchedfiltering. For redundantly modulated carriers (i.e., multiple frequencychannels modulated with the same data symbol), either or bothphase-domain sampling and time-domain sampling may be used. Time-domainsampling may involve combining the modulated carriers to generatesuperposition signals that can be separated via time-domain multi-userdetection. Multi-user detection may include interference cancellation,interference suppression, constellation processing, and/or optimization.

FIG. 11 shows a CI-OFDM signal architecture for a plurality M of users.Each user is provided with a unique set of carriers. A user may becapable of using all available time slots/phase spaces associated withthe set of carriers. Different users may or may not share the samecarrier sets. Coding may be provided to distribute each data symbol overa plurality of carrier sets. Other signal-processing techniquesassociated with OFDM may be incorporated into CI processing. A receivermay employ at least one matched filter to process individual carriersignals or carrier superpositions. A receiver may provide time-domainprocessing, such as sampling, to received signals. For example,superposition signals may be sampled with respect to predetermined timereferences and time intervals.

Another form of CI-OFDM assigns a plurality of frequency-diversecarriers to serve as each OFDM carrier. This form ensures that a singlecarrier is not significantly affected by deep fades and narrowbandinterference. A further adaptation of this CI-OFDM form allows multiplesignals to share each OFDM carrier. Another form of CI-OFDM allows foreach OFDM or CI-OFDM carrier to be spread or coded with a CI/DS-CDMAsignal. In yet another form of CI-OFDM, each data symbol on each carrieris coded. The codes may include CI codes and/or any other form ofcoding. Coding may include at least one of a multiple-access code, aspread-spectrum code, a channel code, an encryption code.

FIG. 12 shows one of many possible CI MC-CDMA architectures. In thiscase, a k^(th) user having a k^(th) phase space φ_(kn) is provided witha spreading sequence c_(kn) in which a binary value is assigned to eachof a plurality N of carriers. Multi-user detection may be employed toseparate interference between the users.

FIG. 13A is a time-domain representation of a plurality K of DS-CDMAcodes generated from a CI architecture. Each chip of the CI DS-CDMAcodes is generated from a CI superposition of carriers. Each chip isprovided with a binary code value corresponding to a DS-CDMA spreadingcode. The chip shape can be adjusted by applying weights to the chip'scarriers. In this case, the chips have a distinctive sinc-like shapethat allows chip overlap (shown in FIG. 13B). Chip overlap doubles thecode length without increasing bandwidth. This can double capacity.Furthermore, CI provides enhanced frequency diversity, narrowbandprocessing capabilities (e.g., spatial processing), and simplifiedsignal processing at both the transmit and the receive sides.

FIG. 13C shows one of many possible carrier architectures for a CIDS-CDMA system. A k^(th) user is assigned a plurality M of phase spaces.Each phase space corresponds to a superposition of carriers that providea chip for the k^(th) user's DS-CDMA code, which has a code length of M.Other users may share the same carriers and phase spaces. However,differences in users' codes provide for separation of the users.

In some applications, as described in Applicant's '992 patent,time-domain and/or frequency-domain shaping may be provided to thecomponent waveforms. In one set of applications, time-domain shaping orwindowing provides side-lobe reduction in the frequency domain.Time-domain shaping may also be employed to shape the main lobe.Similarly, frequency-domain shaping or windowing may be provided toshape either or both the time and frequency-domain characteristics ofthe composite waveforms and/or individual waveform components.

Windows used for either or both time-domain shaping and frequency-domainshaping may be constructed from products, sums, portions, orconvolutions of simple windows and functions. Windows may include one ormore window types, including, but not limited to, rectangle, triangle,cos^(α)(x), Hanning, Hamming, Riesz, Riemann, De La Valle-Poussin,Tukey, Bohman, Poisson, Cauchy, Gaussian, Dolph-Chebyshev,Kaiser-Bessel, Barcilon-Temes, Blackman, and/or Blackman-Harris windows.

In some applications, methods of exploiting known ratios of inter-symbolinterference between overlapping waveforms (e.g., CI components and/orcomposite waveforms) may be exploited to separate the waveforms and/ordetermine symbols modulated on the waveforms. For example, anycombination of cancellation filters and equalizers may be employed tomitigate the effects of inter-symbol interference. Inter-symbolinterference may include any combination of frequency, time,polarization, code, or spatial overlap.

In one set of embodiments of the invention, individual CI components maybe processed to compensate for inter-symbol and/or co-channelinterference prior to combining. For example, an equalizer may beprovided for each carrier to mitigate inter-symbol interference. Anequalizer may follow a matched filter or Fourier transform.

An equalizer may follow a combiner. CI carriers or carrier symbolvalues, once compensated for inter-symbol interference, may be combinedwith respect to any CI combining technique. Similarly, equalization mayoptionally be employed to mitigate the effects of CI pulse or CI symboloverlap. In another set of embodiments, at least one optimal combinermay be employed to mitigate the effects of inter-symbol interference.Optimal combining may employ cancellation, including multi-user and/ormulti-channel detection.

Co-channel interference may be removed via cancellation. Thus,cross-coupled canceling filters may be employed to remove co-channelinterference and/or inter-symbol interference. Co-channel interferencemay be compensated with the aid of a multi-user detector.

CI symbol/carrier generation may be performed using any of variousappropriate polyphase filters. Polyphase filters employed in theinvention may incorporate additional functions, such as, but not limitedto, up sampling and interpolation. Similarly, CI signals may beprocessed in a receiver by one or more polyphase filters, such as atleast one polyphase filter adapted to perform matched filtering and downsampling.

Symbols and/or channels having predetermined or otherwise knowninterference ratios may be transmitted. Transmitted symbols may beintentionally overlapped with respect to time, frequency, space, and/orany other diversity parameters. Transmissions may be distorted byvarious channel effects (e.g., multipath effects, non-linear channeleffects, etc.) to cause interference. In some cases, channelcompensation at either or both the transmitter and the receiver cancause inter-symbol and/or co-channel interference. For example, carriersexperiencing excessive noise and/or interference levels may beeliminated or discarded, resulting in overlap between adjacent CIsymbols or signals. Interference ratios may be determined by anycombination of training, pilot-signal processing, optimal combining,blind adaptive processing, as well as other adaptive techniques.

CI/DS-CDMA Transmitter Overview

Descriptions of CI/DS-CDMA transmission and reception are intended toillustrate the nature of CI processing. As these descriptions areintended to convey a basic understanding of CI and its applications toCDMA, they are not intended to suggest particular method or apparatusembodiments. Many embodiments fall within the scope of the invention.Descriptions of CI/DS-CDMA include particular signal-processingtechniques to convey an understanding of CI principles rather thansuggest any preferred signal-processing methods.

In a CI/DS-CDMA system, a k^(th) user's transmission signal is expressedby:

${{s^{k}(t)} = {b_{k}{\sum\limits_{i = 0}^{N - 1}{\beta_{i}^{k}{h\left( {t - {kT}_{c}} \right)}}}}},$

where b_(k) is a data bit for the k^(th) user, β_(i) ^((k)) is an i^(th)value of a spreading sequence corresponding to the k^(th) user, and h(t)represents a CI-based chip. T_(c) is the chip duration. The data bitb_(k) is typically a binary or M-ary PSK modulated symbol. The data bitb_(k) may be represented by other types of modulation.

The spreading sequence β_(i) ^((k)) is typically a direct-sequence code.For example, values of β_(i) ^((k)) may represent a long code, a Walshcode, a Gold code, a Kasami code, a Barker code, etc. Values of β_(i)^((k)) may represent a CI code, a wavelet code, or some other type ofcode or transform. Values of β_(i) ^((k)) may be binary, polyphase,poly-amplitude, or some hybrid.

The CI-based chip h(t) is typically a CI pulse, as described herein. TheCI-based chip h(t) may have a similar shape to a conventional DS-CDMAchip, such as a raised cosine, Gaussian, or sinc function. However,unlike conventional DS-CDMA chip shapes, which occupy a continuousbandwidth, CI-based chips h(t) are constructed from narrowband carriers.This enables CI/DS-CDMA to benefit from narrowband processing andexploit frequency-diversity reception. Whereas conventional DS-CDMAchips require a wide, continuous frequency band, CI/DS-CDMA can operateacross non-contiguous frequency bands. CI-based chips h(t) may beconstructed from closely spaced or sparsely spaced carriers. The carrierspacing may be incremental and/or non-incremental. Carriers may bepositioned in multiple non-contiguous frequency bands.

The CI-based chips h(t) can belong to any type of code or transform,such as a wavelet transform. DS-CDMA codes may be constructed withrespect to the orthogonal bases defined by a wavelet transform. DS-CDMAcodes may be combined with other types of transforms, such as a wavelettransform. In any of these cases, CI may be used as the basis for thechip h(t). The chip duration T_(c) can depend on the chip spacing.Time-shifted pulses h(t) are orthogonal to each other if they areshifted by some integer multiple of the pulse width:

∫₀^(Ts)h(t − pTc)h(t − qTc) t = 0  (p ≠ q).

The chips h(t−iT_(c)) can also be created by phase offsetting eachn^(th) carrier of the pulse h(t) by 2πn/N.

Time-shifted pulses h(t) are substantially orthogonal(pseudo-orthogonal) to each other if they are shifted by somehalf-integer odd multiple of the pulse width. Similarly, correspondingphase shifts made to the CI carriers effect corresponding orthogonalityconditions. Although the chip may actually extend over at least onesymbol interval, the effective duration as seen in the time domain maybe approximately a chip width (orthogonal case) or half of a chip width(pseudo-orthogonal case).

The basic CI chip shape h(t) can be expressed by:

${{h(t)} = {\sum\limits_{n = 0}^{N - 1}{{A(n)}{\cos \left( {2{\pi \left( {f_{o} + {nf}_{s}} \right)}t} \right)}}}},$

where A(n) expresses the chip shape in the frequency domain. Forexample, A(n) may be a frequency-domain window that shapes thetime-domain characteristics of the chip h(t). In the most basic case,A(n) is constant and the chip shape h(t) is time-limited to one symbolduration T_(s). In cases where a repetitive direct-sequence code isrequired, the chips h(t) in the code may have a much longer durationthan the symbol duration T_(s). In this case, the symbols b_(k) maytime-limit the chip shape h(t). Raised cosines, sinc functions, Gaussianfunctions, and other chip shapes, including wavelets, may be constructedby choosing an appropriate chip-shaping function, such as A(n) and/or atime-domain window function. The basic chip shape may also be expressedby:

${{h(t)}} = {{{A \cdot \frac{\sin \left( {\frac{1}{2}N\; 2\pi \; \Delta \; {ft}} \right)}{\sin \left( {\frac{1}{2}2\pi \; \Delta \; {ft}} \right)}}}.}$

In the orthogonal case, the k^(th) user's transmission signal can beexpressed by:

${s^{k}(t)} = {b_{k}{\sum\limits_{i = 0}^{N - 1}{\beta_{i}^{(k)}{\sum\limits_{n = 0}^{N - 1}{{A(n)}{\cos \left( {{2\; \pi \; f_{o}t} + {2\; \pi \; {{nf}_{s}\left( {t - {iT}_{c}} \right)}}} \right)}{g(t)}}}}}}$

where A(n) is an n^(th) value of a window function that may provide ascalar or complex weight to each CI carrier. A time-domain windowfunction g(t) may provide frequency-domain shaping to the chip shapeh(t). The function g(t) may be a unit-amplitude rectangular waveformhaving a duration of T_(s). The expression for s_(k)(t) can be writtenas:

${s_{k}(t)} = {b_{k}{\sum\limits_{i = 0}^{N - 1}{\beta_{i}^{(k)}{\sum\limits_{n = 0}^{N - 1}{{A(n)}{\cos \left( {{2\; \pi \; f_{o}t} + {2\; \pi \; {nf}_{s}t} - {{ni}\; 2{\pi/N}}} \right)}{g(t)}}}}}}$

where T_(c)ƒ_(s)=T_(c)/T_(s)=1/N. In the pseudo-orthogonal case, theexpression for s_(k)(t) is:

${s_{k}(t)} = {b_{k}{\sum\limits_{i = 0}^{{2N} - 1}{\beta_{i}^{(k)}{\sum\limits_{n = 0}^{{2N} - 1}{{A(n)}{\cos \left( {{2\; \pi \; f_{o}t} + {2\; \pi \; {nf}_{s}t} - {{ni}\; {\pi/N}}} \right)}{g(t)}}}}}}$

The total transmitted signal for K users is:

${S(t)} = {\sum\limits_{k = 0}^{K - 1}{b_{k}{\sum\limits_{i = 0}^{N - 1}{\beta_{i}^{(k)}{\sum\limits_{n = 0}^{N - 1}{{A(n)}{\cos \left( {{2\pi \; f_{o}t} + {2\pi \; n\; f_{s}t} - {{ni}\; 2{\pi/N}}} \right)}{g(t)}}}}}}}$

A CI/DS-CDMA transmitter may be defined as any system that generatesCI/DS-CDMA signals as defined by either equation for the k^(th) user'stransmission signal or the equation representing the total transmittedsignal for K users. Equivalently, a CI/DS-CDMA transmitter may bedefined as any device adapted to generate one or more DS-CDMA signalsmade of N separable frequency components.

The CI/DS-CDMA transmission equations represent various mathematicalrelationships between various components of a transmitted CI/DS-CDMAsignal. Accordingly, the transmission equations do not imply anyparticular order or process for generating CI/DS-CDMA signals. Forexample, one embodiment of the invention modulates a code sequence witha data stream whereas another embodiment impresses data symbols onto acode sequence during code generation. In one set of embodiments,CI/DS-CDMA carriers are generated by redundantly modulating aharmonic-signal source (such as a pulse generator) with data symbols(such as information-modulated code symbols). In another set ofembodiments, individual carriers are modulated (e.g., in an IFFT) togenerate CI/DS-CDMA signals.

A CI transmitter may be implemented via many different techniques. Thepresent invention anticipates design variations of CI-basedtransmitters. A CI/DS-CDMA transmitter, as well as any other CItransmitter, is characterized by the signals generated. In particular, aCI/DS-CDMA transmitter is any device, system, or algorithm capable ofimpressing information onto a plurality of carriers and adjusting (e.g.,weighting) the carriers to provide a superposition signal havingpredetermined time-domain characteristics. Such time-domaincharacteristics may include a signal resembling a direct-sequence code.

The superposition signal may be shaped to produce a lowpeak-to-average-power ratio (PAPR) or crest factor. For example, theindividual carriers may be provided with predetermined or adaptive phaseoffsets to reduce PAPR. The phase offsets may be generated using anycombination of deterministic, adaptive, and random processes. One set ofembodiments employs Schroeder's method to generate carrier-phaseoffsets. Similarly, phase offsets may be provided to CI code chips.

The superposition signal may be shaped to produce other signalcharacteristics, such as predetermined frequency-domain characteristics.In other types of CI-based transmitters, transmitted signals may beshaped with respect to corresponding desired time-domain,frequency-domain, spatial, polarization, and/or any other type ofdiversity-parameter characteristics.

CI/DS-CDMA Receiver Overview

The receiver overview of CI/DS-CDMA signal processing describesparticular signal-processing techniques to convey an understanding of CIprinciples, rather than suggest any preferred signal-processing methods.The mathematical analysis of CI/DS-CDMA signal processing illustratedherein does not necessarily imply any single preferred method or systemfor implementing the present invention. In a Rayleighfrequency-selective slow fading channel, each multi-frequency carriercomprising the CI/DS-CDMA signal experiences a unique flat fade. In thesimple case where all values of A(n) are unity, the received signal isrepresented by:

${r(t)} = {{\sum\limits_{k = 0}^{K - 1}{b_{k}{\sum\limits_{i = 0}^{N - 1}{\beta_{i}^{(k)}{\sum\limits_{n = 0}^{N - 1}{\alpha_{n}{\cos \left( {{2\pi \; f_{o}t} + {2\pi \; {nf}_{s}t} - {{ni}\; 2{\pi/N}} + \varphi_{n}} \right)}{g(t)}}}}}}} + {n(t)}}$

where α_(n) is a gain, φ_(n) is a phase offset for an n^(th) carrier ofa CI pulse resulting from fading, and n(t) is additive white Gaussiannoise. Assuming exact phase synchronization, a decision variableresulting from a received multi-frequency carrier component of eachreceived chip is expressed by:

$r_{m,n} = {{\sum\limits_{k = 0}^{K - 1}{b_{k}{\sum\limits_{i = 0}^{N - 1}{\beta_{i}^{(k)}\alpha_{n}{\cos \left( {{n\; m\; 2{\pi/N}} - {{ni}\; 2{\pi/N}}} \right)}}}}} + n_{m,n}}$

The CI/DS-CDMA receiver for an l^(th) user detects an m^(th) chip ateach carrier as shown in FIG. 18A. The m^(th) chip is separated into itsN carrier components. Each chip and each carrier contribute a decisionvariable r_(m,n) corresponding to

$r_{m,n} = {{b_{l}\beta_{m}^{(l)}\alpha_{n}} + {b_{l}\alpha_{n}{\sum\limits_{\underset{i \neq m}{i = 0}}^{N - 1}{\beta_{i}^{(l)}{\cos \left( {{n\; m\; 2{\pi/N}} - {{ni}\; 2{\pi/N}}} \right)}}}} + {\sum\limits_{\underset{k \neq l}{k = 0}}^{K - 1}{b_{k}\beta_{m}^{(k)}\alpha_{n}}} + {\sum\limits_{\underset{k \neq l}{k = 0}}^{K - 1}{b_{k}\alpha_{n}{\sum\limits_{\underset{i \neq m}{i = 0}}^{N - 1}{\beta_{i}^{(k)}{\cos \left( {{n\; m\; 2{\pi/N}} - {{ni}\; 2{\pi/N}}} \right)}}}}} + n_{m,n}}$

The first term represents the contribution from user l, carrier n, andchip m. The second term represents the other N−1 chips of the user 1.The third term represents interference due to the m^(th) chip of otherusers. The fourth term represents interference from user l's other N−lchips. The fifth term is a zero-mean Gaussian random variable withvariance σ_(n) ²=N₀/2. The terms, n_(m,n), are correlated across chips,but not across carriers.

The covariance matrix of the vector noise (n_(0,n), n_(1,n), n_(2,n), .. . n_(N−1,n)) corresponding to a fixed carrier number n and a variablechip number m is:

$C_{n} = {\frac{N_{0}}{2}\begin{pmatrix}1 & {\cos \left( {2{\pi/N}} \right)} & {\cos \left( {2*2{\pi/N}} \right)} & \ldots & {\cos \left( {\left( {N - 1} \right)*2{\pi/N}} \right)} \\{\cos \left( {2{\pi/N}} \right)} & 1 & {\cos \left( {2{\pi/N}} \right)} & \ldots & {\cos \left( {\left( {N - 2} \right)*2{\pi/N}} \right)} \\\; & \; & \vdots & \; & \; \\{\cos \left( {\left( {N - 1} \right)*2{\pi/N}} \right)} & \; & \; & \ldots & 1\end{pmatrix}}$

Multi-frequency carrier combining is used to combine the r_(m,n) termsacross the carriers, as indicated by the functionality shown in FIG.18A. This results in frequency-diversity benefits when recreating eachchip and removal of the second and fourth interference terms (whichrepresent inter-chip interference).

Orthogonality Restoring Combining (ORC) may be used to remove the secondand fourth interference terms. Each r_(m,n) term is scaled by α_(n) andsummed over n to provide a decision variable R_(m) for an m^(th) chip:

$R_{m} = {\sum\limits_{n = 0}^{N - 1}{r_{m,n} \cdot {1/\alpha_{n}}}}$

However, ORC can result in substantial noise enhancement. Thus, ORC ismost suitable for low-noise conditions (i.e., high SNR).

EGC is preferable for low signal to noise. EGC combines the N carrierterms for the m^(th) chip according to:

$R_{m} = {\sum\limits_{n = 0}^{N - 1}r_{m,n}}$

MMSEC minimizes the second term and the fourth term and optimizesfrequency diversity while minimizing the noise. Using multicarrier MMSECprovides a decision variable R_(m) for an m^(th) chip:

$R_{m} = {\sum\limits_{n = 0}^{N - 1}{r_{m,n} \cdot \left( {\alpha_{n}/\left( {{K\; \alpha_{n}^{2}} + N_{0}} \right)} \right)}}$

A final decision variable D_(l) for user l results from a typicalDS-CDMA combining technique across chips, which eliminates multi-userinterference. Each chip's decision variable R_(m) is multiplied by anm^(th) spreading code β_(m) ^((l)) and combined:

$D_{l} = {\sum\limits_{m = 0}^{N - 1}{R_{m}\beta_{m}^{(l)}}}$

The orthogonal cross-correlation between spreading codes of differentusers minimizes the multi-user interference.

Although the receiver overview describes decision variablescorresponding to each chip and each carrier, preferred embodiments ofthe invention may process either chips or carriers to derive decisionvariables. Chip sequences may be processed to provide a decisionvariable. In one set of embodiments, each carrier may be processed tocompensate for channel effects and decode a particular data stream frominterfering signals. In another set of embodiments, channel compensationis performed at the carrier level, the carriers are combined, and thenthe resulting superposition signal is processed in the time domain. Thetime-domain processing may be supplemented with RAKE reception.

Channel simulations show dramatically improved BER performance when a CIarchitecture is applied to a conventional DS-CDMA system. Because CIexploits frequency-diversity benefits that are inherent in multicarrierpulse shaping, CI does not require a RAKE receiver.

CI/DS-CDMA receivers may include multi-user detectors (MUDs) thatoperate in the time domain and/or the frequency domain. MUDs exploitcross correlations to substantially improve data detection. Thus, MUDscan increase channel throughput (e.g., system capacity) ofinterference-limited systems. MUDs are well known in the art and includevarious designs, such as optimal combiners (e.g., maximum-likelihoodcombiners), linear detectors (e.g., correlators, minimum mean squarederror detectors), and non-linear interference cancellers (e.g.,decision-feedback systems, successive-cancellation systems, Turbo MUDs,etc.).

CI/DS-CDMA MUDs may include space-time and/or space-frequency MUDs thatexploit the spatial characteristics of the propagation environment withrespect to time and/or frequency. Multi-user detection may be performedwith respect to other diversity parameters. A Turbo MUD may be employedthat exploits the multiple-access channel and the temporal structureinduced by channel coding. A Turbo MUD may iterate between multi-userdetection and channel decoding, exchanging soft decisions on symbolinformation at each iteration. Quantum MUDs may be employed to exploitquantum measurements and the multiple-access channel.

CI/DS-CDMA Transceiver System

FIG. 14A shows components of one embodiment of a CI/DS-CDMA transmitter.A symbol generator 1202 receives at least one input data stream from adata source 1200 and at least one code sequence from a code source 1201.The symbol generator 1202 converts the data bits from the input streaminto a plurality N of symbols s_(n), n=1, 2, . . . , N. The symbolss_(n) are optionally stored in a register 1204. The symbols s_(n) mayoptionally be weighted by a weighting system 1211. The weighting system1211 applies a plurality of complex weights w_(n) for channelcompensation, channel coding, sub-channel coding, CI-based coding, PAPRreduction, encryption, multiple-access, or any combination thereof.

A frequency-to-time-domain converter 1206 converts a plurality offrequency-domain symbols into at least one time-domain signal. In thecase where the converter 1206 is a digital system (such as an IFFT, anIOFFT, a digital filter bank, etc.), the output of the converter 1206produces digital time-domain signals x_(N′) that may be stored in ashift register 1208. Optionally, the output signals x_(N′) may beweighted by some complex-weighting system 1213. Optional complex weightsω_(n′) may be employed to provide pre-distortion for channelcompensation and/or implement some additional coding, encryption, etc.Optionally, the output signals x_(N′) may be interleaved prior totransmission.

A transmission system 1210 processes the signals x_(N′) fortransmission. The transmission system 1210 may provide A/D conversion,amplification, up-conversion, modulation, filtering, and/or any othersignal processing typically performed by a transmitter. The transmissionsignals are then coupled into a communication channel (not shown). Acommunication channel, as described herein, typically comprises an RFchannel. However, a communication channel may also comprise othertransmission media, such as modulated laser, waveguide, ultrasound, orfluidic systems. A controller 1205 receives a clocking signal from aclock 1207. The controller 1205 regulates timing and synchronization ofoperations performed by the components shown in FIG. 14A.

The symbol generator 1202 may perform interleaving and/or channelcoding. The code source 1201 may include one or more sets of CI codesthat may be used for channel coding, multiple access, spread spectrum,encryption, etc. In one set of embodiments, the code source 1201 isadapted to provide a conventional direct-sequence code to the symbolgenerator 1202. The symbol generator 1202 generates appropriate carrierweights to provide the CI superposition signal produced by the converter1206 with appropriate time-domain characteristics of a direct-sequencesignal. Similarly, other types of CI-based time-domain signals may begenerated using the CI/DS-CDMA transmitter shown in FIG. 14A.

In another set of embodiments, CI codes are generated by the code source1201. In yet another set of embodiments, one or more direct-sequenceand/or CI codes are applied as weights in either or both weightingsystems 1211 and 1213. Applied codes may include one or moremultiple-access, channel, spreading, and/or encryption codes.

The converter 1206 may perform any type of transform to generate amulticarrier signal. Although the converter 1206 is illustrated as afrequency-to-time converter, other types of converters may beimplemented with respect to the definition of a multicarrier signal. Inone embodiment, the converter 1206 is a beam-forming system.

In another embodiment, the converter includes a multi-port system thatconveys each of a plurality of symbols to a different transmitter. Thetransmitters may be spatially separated. The transmitters may becharacterized by different polarizations or otherwise have differenttransmission characteristics.

The converter 1206 may convey symbols to different types of subcarriers.For example, the symbols may modulate various orthogonal orquasi-orthogonal circular-polarized and/or elliptical-polarizedcarriers. Orthogonality between different polarized carriers may becharacterized by different rotation rates, different directions ofrotation, and/or orthogonal (e.g., perpendicular) polarization vectorsin two or three dimensions.

The symbol generator 1202 may form data symbols and/or CI carrierweights via orthonormal-basis vectors. For example, if data symbols aregenerated from an 8-chip Hadamard-Walsh matrix, each of the eight rowvectors (i.e., Walsh codes) of the matrix can be expressed by a linearcombination of three orthonormal basis vectors:

$\quad\begin{matrix}\left\lbrack 1 \right. & 0 & 1 & 0 & 1 & 0 & 1 & \left. 0 \right\rbrack \\\left\lbrack 1 \right. & 1 & 0 & 0 & 1 & 1 & 0 & \left. 0 \right\rbrack \\\left\lbrack 1 \right. & 1 & 1 & 1 & 0 & 0 & 0 & \left. 0 \right\rbrack\end{matrix}$

Different combinations of the basis vectors (e.g., modulo-two additions,multiplications) can provide all eight Hadamard-Walsh codes.Furthermore, since the first four values of each orthonormal-basisvector are identical to the second four values (in the case of the thirdvector, the second four values are inverted relative to the first fourvalues), only four values need to be stored for each vector. Theall-ones vector does not need to be stored. Various matrices, includingHadamard-Walsh matrices, may be represented by a reduced set of vectors,such as orthonormal-basis vectors.

In one set of preferred embodiments, a CI-based signal is provided withsymbols modulated onto various phase spaces. FIG. 15A represents carrierphases of a plurality of CI carrier frequencies ƒ_(n) corresponding to aplurality of orthogonal phase spaces Ps(n′). Orthogonal phase spaces areseparated by a pulse width T_(ps)=1/(ƒ_(s)N) whereas quasi-orthogonalphase spaces are separated by a half pulse width T_(ps)=1(ƒ_(s)2N). EachCI carrier frequency ƒ_(n) is expressed by: ƒ_(n)=ƒ_(o)+nƒ_(s). AtPs(0), each carrier has an arbitrary phase φ_(n).

FIG. 15B shows a matrix that represents contributions of phase-shiftedsymbol values s_(n′) to each carrier frequency ƒ_(n) for each of aplurality of phase spaces Ps(n′). The columns correspond to phase spacesand the rows correspond to carrier frequencies ƒ_(n). Severalsimplifying assumptions are made with respect to FIG. 15B. The arbitraryphases φ_(n) are zero and baseband signal processing is assumed (i.e.,the frequency-offset ƒ₀ is zero).

Each of a plurality of CI pulses (represented by the orthogonal phasespaces Ps(n′)) is modulated with a particular symbol value s_(n′). Eachphase space Ps(n′) is characterized by a unique set of phase offsetsapplied to the carrier frequencies ƒ_(n). Since each phase space Ps(n′)is defined by a plurality of phase offsets to the same set of carrierfrequencies ƒ_(n), a symbol s_(n′) applied to one phase space interfereswith symbol values applied to at least some of the carrier frequenciesƒ_(n) in the other phase spaces Ps(n′). In CI, the interfering symbolvalues cancel each other and the desired symbol values combinecoherently when the carriers are combined in a particular phase spacePs(n′). Thus, a combination of symbols s_(n′) and related phase offsetscontribute to a complex value v_(n) associated with each frequencyƒ_(n). This complex value v_(n) is the sum of row elements shown in FIG.15B for a corresponding frequency ƒ_(n).

The matrix elements shown in FIG. 15B illustrate basic mathematicalrelationships between carrier frequencies ƒ_(n) and phase spaces Ps(n′)that can simplify transforms between frequency-domain and time-domainsignals. For example, given a set of symbol values s_(n′), thesemathematical relationships provide carrier-frequency weights thatproduce a superposition signal with time-domain characteristicscorresponding to the symbol values s_(n′).

For a particular frequency bin ƒ_(n), a corresponding phase-space vectoris shown as follows:

ƒ_(n):[1e ^(i2πT) ^(ps) ^(nf) ^(s) ,e ^(i2π2T) ^(ps) ^(nf) ^(s) . . . e^(i2π(N−1)T) ^(ps) ^(nf) ³ ]

This vector represents n full rotations in the complex plane. Each valuein the vector corresponds to a particular phase space Ps(n′). Eachphase-space value Ps(n′) is multiplied by a corresponding data-symbolvalue s_(n′). The sum of the data-modulated phase-space values providesan effective complex weight w_(eff)(n) for frequency bin ƒ_(n). Thus,column vectors (i.e., phase spaces Ps(n′) and their corresponding symbolvalues s_(n′)) are summed to generate the complex values w_(eff)(n)associated with row vectors (i.e., frequency bins ƒ_(n)).

A corresponding inverse transform may be provided. For example, areceiver may measure complex values w′_(eff)(n) corresponding to eachcarrier frequency ƒ_(n). The complex values w′_(eff)(n) represent theeffective complex weight w_(eff)(n) after it has been distorted by thechannel and/or the receiver. Since the phase spaces Ps(n′) are easilydetermined via column vectors of the matrix shown in FIG. 15B, themeasured complex values w′_(eff)(n) can be weighted (e.g., shifted) andsummed to estimate the symbols s_(n′) transmitted in corresponding phasespaces Ps(n′).

The column and row vectors of the matrix shown in FIG. 15B are similarto each other in the absence of symbol values s_(n′). Linearcombinations of an orthonormal basis may be used to characterize thecolumn and/or row vectors. For a set of vectors of length N, a linearcombination of orthonormal-basis vectors may include modulo-N additionsbetween two or more vectors, vector products, corresponding phaseshifts, or equivalent operations. A set of orthonormal basis vectors forFIG. 15B is shown as follows:

ƒ₁: [1e ^(i2πT) ^(ps) ^(f) ^(s) . . . e ^(i2π(N−1)T) ^(ps) ^(f) ^(s) ]

ƒ₂: [1e ^(i2πT) ^(ps) ^(2f) ^(s) . . . e ^(i2π(n−1)T) ^(ps) ^(2f) ^(s) ]

ƒ₄: [1e ^(i2πT) ^(ps) ^(2f) ^(s) e ^(i2π2T) ^(ps) ^(4f) ^(s) . . . e^(i2π(N−1)T) ^(ps) ^(4f) ^(s) ]

The vector corresponding to each n^(th) frequency ƒ_(n) represents nrotations in the complex plane. In one embodiment, orthonormal vectorsrepresenting n=2^(m) rotations in the complex plane (where m=0, 1, 2, .. . ) are stored in memory. The storage space required for each vectorcan be reduced by considering vector symmetry. In another embodiment,each orthonormal vector is generated. In one aspect of the invention,the vector representing one rotation in the complex plane serves as thebasis to build other vectors, such as the orthonormal-basis vectors.

FIG. 14B illustrates components of one embodiment of a CI/DS-CDMAreceiver.

At the receiving end of a transmission link 113, a receiver system 1216couples transmitted signals from at least one communication channel (notshown). The received signals are typically filtered, amplified,down-converted, and digitized by the receiver system 1216. Reception mayinclude beam forming, any of various types of sub-space processing,space-time processing, space-frequency processing, channel compensation,and/or demultiplexing. The digitized received time-domain signals mayoptionally be coupled into a register 1218. An optional weighting system1219 may apply weights to the time-domain signals prior to processing bya time-domain-to-frequency-domain converter 1220.

Each set of N time-domain values in register 1218 is converted via thetime-domain to frequency-domain converter 1220 to generate a set offrequency-domain symbols s′_(n). This transformation is the inverse ofthe transformation generated by the frequency-to-time-domain transform1206. The communication link (not shown) will typically attenuate and/orphase shift the signals represented by x_(n). The received signal valuesy_(n) and s′_(n) usually differ from the transmitted signal values s_(n)and x_(n).

A filter bank or Fourier transform may be implemented as a bank of Nsingle-pole filters (i.e., resonators) in which each n filter has a poleat a corresponding n^(th) frequency ƒ_(n). The invention may employ theGoertzel algorithm, which exploits the periodicity of the phase factorsin a DFT, to perform a DFT computation as a linear filtering operation.The Goertzel algorithm is typically preferable when the DFT to becomputed has a relatively small number M of values, where M≦log₂ N.Similarly, various aspects of the invention that employ periodic phaseterms, such as CI coding, CI sampling, OFFT operations, phased-arrayprocessing, etc., may employ the Goertzel algorithm to providefiltering.

Each CI data symbol can be obtained by coherently processingcorresponding CI components. Preprocessing is typically performed toremove the carrier frequency ƒ_(c) from the received signal. Eachreceived signal can be processed to form an in-phase/quadrature-phasepair. The processed signals may be compensated for channel effectsand/or receiver processing variations. The processed signals may thencompressed by a DFT process, such as an FFT.

One or more sinc filters, such as digital sinc filters, may be used togenerate CI sub-carrier frequencies. For example, data symbols may bemodulated onto individual time-domain sincs or pulses. Filterscharacterized by periodic time-domain characteristics may be employed togenerate multicarrier signals. Similarly, periodic filters may be usedto process received CI signals. Various filter shapes, includingGaussian-shaped filters, may be employed.

The frequency-domain symbols s′_(n) may be stored in a register 1222. Anoptional complex-weighting system 1224 or an equalizer (not shown) maybe used to compensate for attenuations, phase shifts, and/orinter-symbol interference. The frequency-domain symbols s′_(n) arecoupled to a symbol decoder 1228 that may optionally store the symbolsS′_(n) in a buffer (not shown). The symbols s′_(n) are decoded togenerate an estimate of the original data stream. Additional dataprocessing and/or system control may be performed by an optional datasink 1230. The data sink 1230 may include one or more feedback loops,optimal combiners, multi-user detectors, hard-decision systems,soft-decision systems, error-detection systems, and/or error-correctionsystems.

A system controller 1231 is provided with a clock signal from a clock1233. The controller 1231 regulates timing of signal-processingoperations performed by a plurality of the receiver components. Atransceiver may employ the same controller and/or clock for bothtransmission and reception.

The symbol decoder 1228 may perform inverse coding operations withrespect to coding applied at a transmitter. The symbol decoder 1228 mayperform adaptive decoding. The symbol decoder 1228 may perform partiallyblind adaptive coding with respect to transmitted data symbols, codes,and/or channel estimates. The symbol decoder 1228 may be adapted toperform de-interleaving, decoding, adaptive decoding, and/or channelcompensation.

The symbol decoder 1228 may generate or otherwise be provided with atleast one CI code, binary direct-sequence code, spreading code, channelcode, encryption code, time and/or frequency-hopping code,pulse-position modulation code, etc. The symbol decoder 1228 may performde-multiplexing, de-spreading, and/or converting at least one signalfrom one phase space to another phase space. The symbol decoder 1228 maydecode a CI-based signal, a CI-coded signal, a direct-sequence signalthat employs CI codes, a direct-sequence signal implemented with CIchip-shaping, any CI-based signal with channel codes, a signalimplemented with CI-based channel codes, a signal implemented with CIcodes for any type of multicarrier CDMA, CIMA signals, CI signals codedwith phase codes to achieve low PAPR, CI signals provided with signalmasking, and/or CI-based and/or CI-coded signals provided withfrequency-hopping.

Reference (e.g., despreading) codes are typically set equal to the codes(or complex conjugates of the codes) at the other ends of the link andonly maximize the SNR of the decoded signals. In one set of embodimentsof the invention, such operation is performed blindly. Transmitted codesmay include weights applied at individual transmitter-array elements forspatial processing, channel compensation, etc. Received codes mayinclude weights applied at receiver-array elements to provide spatialprocessing, channel compensation, etc. Codes may include weights appliedto different signal components (e.g., frequencies, polarizations, codes,code chips, and/or any other diversity-parameter values of one or moresignals) at either or both the transmitter and the receiver. Either orboth coding and decoding operations may be performed usingblind-adaptation techniques.

The transmit codes and channel distortions need not be known at thesymbol decoder 1228. This simplifies the processing used within thenetwork by allowing use of unknown codes at the transceivers in thenetwork. This also allows the use of adaptively determined codes thatare continually optimized to mitigate noise, interference, and/orchannel distortion encountered by the transceiver. Reference codesgenerated at the receiver may be adapted with respect to one or morecharacteristics of received signals. Transmitted codes generated at thetransmitter may be adapted with respect to some reference, pilot, orfeedback signal received from the receiver. Either or both thetransmitter and the receiver may perform channel estimations that areused to adjust codes.

Preferred embodiments of the invention may use non-blind or calibratedtechniques (e.g., least-squares techniques) that use knowledge of thebaseband data sequence, channel distortion, and/or codes to developideal weights based on optimal signal estimation methods. Otherpreferred embodiments may use blind or non-calibrated techniques thatuse more general properties of the data signals to adapt code weightsand/or decoding weights. Combinations of these techniques that use knownand unknown components of the data signal, the code, and/or thetransmission channel can also be used to construct an effectivesolution. Examples of blind techniques that are particularly usefulinclude constant-modulus, multiple-modulus, and decision-directiontechniques. These blind techniques use the message symbol constellationto adapt the decoding weights. A number of methods can be used to adaptmulti-element, multi-frequency, and/or any othermulti-diversity-parameter weights in or prior to the decoder 1228.Dominant-mode prediction (DMP) methods can exploit known packet arrivaltimes, fading characteristics, or known coding parameters of amulticarrier signal. Code-gated self-coherence restoral (SCORE) methodsexploit the known self-coherence (non-zero correlation between thespectrally separated signal components) in the multicarrier signal.

On the transmitter side of a multi-diversity parameter system (e.g.,antenna array, multi-frequency, and/or any multi-valueddiversity-parameter set having similar or identical sets of interferingsignals), directive or retrodirective adaptation methods can be used toeither direct returning signals of interest back to the transmit sourcewith maximum power and/or minimum transmitted radio signals (directivemode), or to jointly direct the returning signals-of-interest back tothe transmit source with minimum radiation in the direction ofinterfering sources (retrodirective mode). Processors can be used toaccurately measure the received signal-of-interest steering vector(e.g., beam pattern, sub-space pattern, frequency-domain pattern,polarization-domain pattern, etc.) and direct a maximal beam back to theother end of the communication link without knowledge of the receivedsignal-of-interest characteristics (e.g., direction-of-arrival,frequency profile, polarization profile, code, etc.) even though theinterference sources completely cover the signal-of-interest passbandand packet interval.

In some embodiments of the invention, it is preferable that each CIcarrier be sufficiently narrow to allow the distortions in thatsub-channel to be modeled by a single phase shift and attenuation. It isalso preferable that CI carriers be sufficiently narrow to ensure that asub channel that is turned off to prevent interference from narrow-bandsources does not unduly waste bandwidth beyond that corrupted by theinterference source. However, narrow channels increase system latencyand the computational complexity of the frequency-domain-to-time-domaintransformation and its inverse. Thus, it is preferable to achieve abalance between the benefits and drawbacks of various sub-channelwidths. In one set of preferred embodiments, narrower subchannels areemployed for frequencies having greater attenuations and/or phaseshifts. Wider subchannels are used at frequencies with reducedattenuations and/or phase shifts.

FIG. 16A illustrates basic components of a CI transmission system. Adata source 1600 supplies a data stream to a symbol generator 1602 thatgenerates symbols relative to the data stream and one or more CI codes,multiple-access codes, spread-spectrum codes, interleaving codes,error-detection codes, and/or channel codes. The symbol generator 1602may generate symbols with respect to a CI/DS-CDMA code. A symbolgenerator, such as the symbol generator 1602, may be adapted to modulatethe symbols. The symbols are modulated with respect to any modulationtechnique, such as phase modulation, frequency modulation, amplitudemodulation, polarization modulation, time-offset modulation, and/or anycombinations thereof. The symbols are impressed onto carriers generatedby a carrier generator 1606.

In one embodiment, the carrier generator 1606 produces carrierfrequencies that are processed with respect to the symbols. In anotherembodiment, the carrier generator 1606 produces periodic time-domainpulses that are modulated with symbols. The output of a periodic-pulsegenerator is a multi-frequency signal. However, the symbols used tomodulate the pulses reflect the desired time-domain structure of thetransmitted signal. Nevertheless, the frequency-domain profile of thetransmitted time-domain signals are similar to a frequency-domain signalcoded with corresponding polyphase signals. These frequency-domaincharacteristics differ from the conventional DS-CDMA frequency-domainstructure, which is single carrier.

The modulated carriers are processed by a transmission system 1610 priorto being coupled into a communication channel (not shown). Thetransmission system 1610 may perform typical signal-processingoperations corresponding to various parameters including channelcharacteristics, required transmission power, transmit frequency,receiver location, acceptable bandwidth, etc. In some embodiments, thecarrier generator 1606 may perform one or more tasks of the transmissionsystem 1610 (e.g., frequency up-conversion). For example, the carriergenerator 1606 may include harmonic-generation capabilities coupled to apassband filter.

FIG. 16B illustrates a more detailed embodiment of a CI transmitter. Acode source 1601 is coupled to the symbol generator 1602. In FIG. 16A,the symbol generator 1602 was assumed to provide codes. The carriergenerator 1606 is illustrated as an inverse Fourier Transform (IFT).This is one of many different carrier generators that may be implementedin a CI transmitter.

FIG. 16C illustrates one particular embodiment of a CI transmitter. Thedata source 1600 and the carrier generator 1606 are coupled to amodulator 1609. The carrier generator 1606 produces carriers havingproperties that reflect one or more input codes generated by the codesource 1601. For example, the code source 1601 may generate polyphasesymbols with respect to a CI code. The code source 1601 may generatesymbols with respect to other code types in addition to, or instead of,CI codes.

The modulator 1609 modulates data bits or symbols onto the carriers.Typically, the carrier generator 1606, such as shown in FIGS. 16A and16B, impresses data symbols onto the carriers. In some embodiments, thesymbol generator 1602 may impress data bits or symbols onto code symbolsvia modulation or a code-generation process.

FIG. 16D illustrates basic components of a particular set of embodimentsof a CI transmitter. The carrier generator 1606 is illustrated as asub-space carrier generator. The carrier generator 1606 may distributecodes corresponding to each data symbol across multiple transmitters.For example, each transmitter of an array may transmit a different codesymbol corresponding to the same data symbol. Preferably, the codesymbol is generated from a CI code or CI/DS-CDMA code. Each code symbolmay be provided to each of a plurality of transmitters to generate adifferent beam pattern or sub-space channel corresponding to each codesymbol. Other types of subspaces may be employed. Subspaces may begenerated from any set of diversity-parameter values that overlap. Forexample, subspaces may be generated from signal polarizations (e.g.,linear, circular, and/or elliptical polarizations), signal frequencies,signal phases, amplitude distributions, etc.

FIG. 16E illustrates generalized components of a broad class of CItransmitters. The carrier generator 1606 is a system that generatescarriers characterized by one or more diversity-parameter values and/orsub-space values.

Different CI codes may be characterized by polyphase projections ontotwo orthogonal diversity-parameter values. Specifically, in-phase andquadrature-phase magnitudes may be expressed by corresponding signalvalues impressed onto orthogonal diversity-parameter values orsubspaces. For example, in-phase and quadrature-phase values maycorrespond to values imparted to vertical and horizontal linearpolarized signals. Similarly, other orthogonal diversity-parametervalues may be used.

CI carriers may be implemented with dynamically changing values impartedto in-phase and quadrature-phase components of any pair of orthogonaldiversity-parameter or sub-space values. In one preferable set ofembodiments, the in-phase and quadrature-phase components arecharacterized by an orthogonal set of sinusoids. The sinusoids representsub-carrier modulations. For example, circular polarization results fromin-phase and quadrature-phase sub-carrier modulation applied to verticaland horizontal linear-polarized signals. To maintain orthogonality, thefrequency spacing ƒ_(s) between the sinusoidal signals is inverselyproportional to the symbol duration. These carriers are then processedto generate superposition signals having predetermined time-domaincharacteristics.

Generation of a CI-based signal may include providing the superpositionof CI carriers with a circular or elliptical polarization. Thepolarization-rotation rate may be selected with respect to multipathdelay profiles to reduce multipath fading. Predistortion of acircular-polarized CI signal may include providing ellipticalpolarization to the transmitted signal. In one set of embodiments, eachCI carrier frequency is expressed as a polarization-rotation rate of acircular-polarized or elliptical-polarized signal. In another set ofembodiments, each CI carrier has the same polarization-rotation rate,but may have different phase offsets. In yet another set of embodiments,each CI carrier frequency is provided with a uniquepolarization-rotation rate. CI codes CI/DS-CDMA, and/or other orthogonalcodes may be applied to (linear, circular, elliptical, etc.) polarizedsignals. Phase coding may be applied in the form of a polarization-phaseoffset, a frequency-phase offset, or an offset to any other set ofdiversity parameter-values that indicates a phase offset.

In CI embodiments that employ orthogonal polarization-rotation rates,the polarized signals are processed in the same way as orthogonalcarrier frequencies. For example, a receiver adapted to process receivedpolarized CI signals may include a filter bank, a transform processor(e.g., any type of Fourier transform, including an orthogonal-frequencyFourier transform), a correlator, a complex-conjugate processor, and/ora sample-and-add system.

Multi-rate circular polarized signals may be implemented as wavelets.Polarized signals may be used in corresponding wavelet-transformoperations. For example, wavelet families may be generated frompolarized signals having durations that are inversely proportional totheir polarization-rotation rates. Orthonormal wavelet bases may begenerated via appropriate selections of scaling factors (i.e., scalingfactors that are proportional to each other by powers of two). Waveletfilters may be implemented with circular and/or elliptical polarizedsignals. Orthonormal wavelet bases, such as polarization-based wavelets,may be used as code chips. Codes, including, but not limited to,multiple-access, spread-spectrum, and channel codes, may be generatedfrom polarization-based wavelet chips. Wavelet chips may be providedwith phase offsets to generate code chips, such as CI code chips.

Polarization-based wavelets may be shaped with respect to time-domainfilters. Multiple signals having different polarization-rotation ratesmay be used to construct wavelets via superposition.Polarization-wavelet characteristics, such as shape, effectivefrequency, duration, etc., can be adjusted by providing weights to thewavelet sub-carriers. Polarization-based wavelet sub-carriers areanalogous to CI carriers. Multiple signals having differentpolarization-rotation frequencies may be combined to construct codechips or other signals having predetermined time-domain characteristics.Weights provided to polarization-based sub-carrier signals may shapedesired time-domain characteristics of the superposition signal.

FIG. 16F illustrates basic components of a CI transmitter that impressesat least one data sequence, at least one channel code, and at least onemultiple-access code onto a plurality of carriers. A carrier generator1606 generates at least one carrier signal. The at least one carriersignal may be replicated by an optional carrier duplicator. A modulatorreceives inputs from a data source 1600, a multiple access code source1601A, and a channel-code source 1601B. Optionally, the multiple accesscode source 1601A may include a spread spectrum code source.

In one set of embodiments, the multiple access code source 1601Aproduces a code for a CI/DS-CDMA signal. In another set of embodiments,the multiple access code source 1601A generates a CI code. In anotherset of embodiments, the channel-code source 1601B generates a CI code.

The modulator 1609 performs any necessary combining of the input signalsand impresses the signals onto the carriers. The carriers are optionallyprocessed by a transmission system 1610 that couples the modulatedcarriers into a communication channel (not shown).

FIG. 17A illustrates the multi-dimensional nature of coding provided toa CI/DS-CDMA signal produced by a CI transmitter. CI code chips c₀, c₁,. . . , c_(N−1) used to modulate individual carrier frequencies producesa carrier superposition a time-domain profile indicative of code chipsc′₀, c′₁, . . . , c′_(M−1). The time-domain code may be a conventionaldirect-sequence code, a channel code, a CI code implemented as amultiple-access, spreading, and/or channel code, or any combinationthereof. In one set of embodiments, the frequency-domain code may be abinary direct-sequence code and the time-domain code may be a CI code.In various embodiments of the invention, frequency-domain and/ortime-domain chips may be interleaved in the time domain.

FIG. 17B illustrates CI coding applied to a multi-dimensional signal. Inone set of embodiments, a polyphase CI code c₀, c₁, . . . , c_(N−1) isapplied to a set of carrier frequencies provided to an antenna array.Each data symbol is expressed by a code-chip value c′₀, c′₁, . . . ,c′_(M−1) corresponding to a different orthogonal diversity-parametervalue, such as a different subspace. In another set of embodiments, thecode-chip values c′₀, c′₁, . . . , c′_(M−1) are impressed upon carriersuperpositions. The code chips c′₀, c′₁, . . . , c′_(m−1) are expressedas orthogonal values of at least one diversity parameter.

FIG. 17C illustrates a three-dimensional diversity-parameter space. Eachaxis represents values of a different diversity parameter d_(n).Orthogonal values are represented by a three-dimensional diversityparameters d_(xyz). Diversity parameters in the diversity-parameterspace may be modulated or otherwise impressed with at least one set ofCI codes. One or more diversity parameters may represent a superpositionof diversity-parameter values. For example, a time-domain axis or aphase-space axis can represent a superposition of multiple carrierfrequencies.

In two dimensions, an instantaneous representation of a conventionalstacked-carrier protocol transmitted and received by antenna arrays canbe represented by an NXM matrix of subcarriers, where N is the number offrequencies and M is the number of array elements at the receiver. Thematrix elements can be modulated with at least one CI code. A CI codemay be applied across frequencies (for example, to produce a CIsuperposition signal or a CI-based MC-CDMA signal), across subspaces, oracross both. Time introduces a third axis to produce an NXMXL space. CIcode chips may be positioned across frequencies, subspaces, and/or timeintervals. Multiple CI codes may be interleaved with respect to anydiversity parameters.

A DS-CDMA code (a first dimension) may be modulated by another code (asecond dimension). Thus, the first-dimension DS-CDMA code may beregarded as a carrier for the second code. In one embodiment of theinvention, a binary-phase (0, π) DS-CDMA code is modulated with a secondpseudo-noise code, such as a PSK code having a magnitude range withinsome small fraction of π. Either code may include a CI-based DS-CDMAcode and/or a CI code. In another embodiment of the invention, thesecond code is a coherence-multiplexing code or some other code (e.g., anoise-like code) characterized by one or more code lengths. Similarly,DS-CDMA, CI, and/or CI/DS-CDMA codes may be impressed upon acoherence-multiplexing code, a code-length division multiple accesscode, or some other noise-like code.

Multi-dimensional codes may include codes derived from channelcharacteristics between at least one predetermined transmitter-receiverpair. For example, multipath and/or at least some other channelcharacteristics are typically unique for each transmitter-receiver link.Thus, link characteristics can be used to assign some form of coding toeach transceiver. Link-characteristic coding may include CI codes and/orCI-based codes.

CI/DS-CDMA Array Processing

FIG. 18B illustrates components of a CI receiver, such as a CI/DS-CDMAreceiver. A receiver system 1816 couples transmitted CI signals from acommunication channel. Receiver processing, such as filtering, downconversion, amplification, beam forming, etc., converts the coupledsignals into electronic received signals. The received signals areprocessed in a time-to-frequency-domain converter 1820 that outputs datasymbols modulated on the individual carriers. If the receiver system1816 includes an antenna array and the converter 1820 providestime-to-frequency-domain conversion for each array element, thefrequency-domain symbols may include multiple-access and/ormulti-channel interference.

Various effects, such as multipath, receiver characteristics, andtransmitter characteristics (e.g., array element spacing, beamdirectionality, spatial gain distributions, etc.), ensure that at leastsome of the interfering signals can be separated from each other.Diversity, such as spatial diversity, can be used to improve signalquality, increase bandwidth efficiency, or achieve some trade offbetween improved signal quality and increased throughput.

The interfering signals are coupled into a diversity combiner 1827 thatcombines the signals to generate desired signals having minimum noiseand interference. The signals received by the separate antennas areindependently demodulated before being applied to the combiner 1827.

Demodulation, as used herein, may include synchronous demodulation,which may be performed with the aid of carrier and timing informationderived from one or more received waveforms. A demodulator may provideone or more additional signal-processing operations, including, but notlimited to, channel selection, bandwidth reduction, despreading,resampling, spectral equalization, matched filtering, timing/phaserecovery.

The number of spatial sub-channels that can be processed by the combiner1827 is typically equal to the number of receiver array elements. WhenCI is used with antenna arrays, array combining systems, and CIdiversity combiners may be combined into a single diversity combiner,such as combiner 1827.

A weight-generation system 1830 provides weights to the diversitycombiner 1827. An adaptive antenna array may include an MMSE diversitycombiner or some other form of optimal combiner. The weight-generationsystem 1830 may select parameters accurately describing channelcharacteristics that minimize the mean squared error of the receivedsignal, which decreases the signal error rate, suppresses interference,and maintains signal quality. These parameters may be estimated.

Parameters needed to optimize performance for diversity combining and/orsub-channel processing are typically determined from channel estimatesand the instantaneous correlation of the received signals. Channelestimations may employ a multiple-pass system (not shown) to account forpast, present, and future channel estimations. Because future referencesmay be determined from a preceding pass, it is possible to refinechannel estimations and accordingly achieve better weights. Theweight-generation system 1830 may include a parameter estimator (notshown) adapted to process either or both the demodulated receivedsignals prior to decoding and the combined received signal afterdemodulation and decoding by the receiver.

A symbol decoder 1828 decodes data symbols and provides blocks ofundecoded symbols and/or decoded symbols to the weight-generation system1830. Symbol decoding may include channel decoding, demultiplexing,deinterleaving, error correction, etc. The symbol decoder 1828 mayperform iterative decoding. In a CI/DS-CDMA system, the symbol decoder1828 performs decoding with respect to the impressed DS-CDMA code.

Each received symbol may be evaluated with respect to a minimum meansquare error or some other performance measurement. The minimum meansquare error is a measure of error probability in a signal based on themean value of the square of the error, (y−{tilde over (y)})², where{tilde over (y)} is any estimate of y. In general, if y is a randomvariable having a mean value of y, then choosing {tilde over (y)}= yminimizes the mean square error. Typically, it is necessary to estimatey based on supplied parameters. The accuracy and usefulness of theestimated mean square error is related to the quality of the parametersused in the estimation.

FIG. 18C illustrates a CI receiver that represents a set of embodimentsof the invention. An input coupler 1840 (such as an antenna) receivessignals from a communication channel (not shown). The input coupler 1840may be coupled to one or more receiver components, such as amplifiersand filters. In particular, a low-noise amplifier 1842 is provided toamplify a received signal. The amplified signal is coupled to anoptional filter-and-down-convert component 1844. The component 1844 mayinclude a multi-stage frequency converter (not shown).

A variable-gain amplifier 1846 is shown coupled to an automatic gaincontrol (AGC) and digital filter assembly 1850. An A/D converter 1848converts the analog gain-adjusted signal to a digital signal. The AGCand filter assembly 1850 separates the digital signal into a pluralityof sub-carrier digital baseband signals that are combined in a combiner1852.

The A/D converter 1848 may optionally include a delta-sigmaarchitecture. One set of delta-sigma architectures employs a feedbackloop to provide a suitable over-sampling ratio. The A/D converter 1848may optionally incorporate at least one band-pass filter in the feedbackloop to allow the A/D converter 1848 to sample at an intermediatefrequency. For example, the A/D converter 1848 may include a filterbank, such as a signal processor adapted to perform a Fourier transform,wavelet transform, or an equivalent operation.

Various system elements not shown may be incorporated into the receiverand/or the receiver components. For example, one or more synthesizers(not shown) may provide clock and/or local-oscillator signals. Thereceiver may include one or more phase-lock loops (PLLs) and/or tunablenotch filters (not shown). In various embodiments of CI receivers, phaseoffsets (such as offsets resulting from timing mismatches,channel-induced phase offsets, clock drift, etc.) may be tracked andcompensated with a PLL.

A weight generator (not shown) may be provided to calculate and/or applyweights to the subcarriers. Weights may be applied during A/D,filtering, and/or combining operations. Frequency offsets affecting thereceived signals may be compensated by one or more operations includingcarrier weighting, MUD, multi-channel detection, frequency translationat either or both the receiver and the transmitter, and adaptablecombining. A symbol decoder (not shown) may follow the combiner 1852.The symbol decoder (not shown) may provide soft-decision control to theweight generator (not shown) and may incorporate a feedback loop.

Various combinations of array processing and multicarrier protocols(such as described in U.S. Pat. Nos. 6,128,276, 5,671,168, 5,528,581,5,973,642, 6,144,711, 6,211,671, and 6,008,760, which are herebyincorporated by reference) may be adapted for use with CI-basedprotocols to provide unusual improvements to system performance, signalquality, and throughput. CI may be implemented with variousarray-processing systems and techniques including, but not limited to,layered space time, space-frequency, spatial interferometry,vector-processing, matrix-processing, frequency diversityinterferometry, marginal-isolation, beam-forming, interference-nulling,beam-steering, and blind adaptive array processing systems and methods.CI may be introduced to array processing systems and methods, such asdescribed in U.S. Pat. Nos. 5,642,353, 5,592,490, 5,515,378, and5,471,647, which are hereby incorporated by reference. CI may beimplemented in array processing systems that provide any combination ofdiversity combining and sub-channel processing.

FIG. 19A is a basic block diagram of a CI-based receiver implementedwith a receiver array. A plurality of array elements 1916.1 to 1916.Pare responsive to transmitted CI signals in order to generate aplurality of electronic receive signals. The transmitted signals may betransmitted from multiple, spatially separated, independent transmitters(e.g., mobile transceivers), multiple independent, co-locatedtransceivers, a single transceiver adapted to transmit signals on aplurality of interfering channels, and/or a plurality of substantiallyco-located transceivers adapted to transmit data symbols on a pluralityof interfering channels.

The receive signals are processed by a time-to-frequency converter (suchas a plurality of FFTs 1920.1 to 1920.P) that separate the receivesignals into a plurality of CI carrier-frequency components. Thecarrier-frequency components are coupled into a diversity combiner 1927that includes a frequency combiner 1925 and a CI combiner 1929. Thefrequency combiner 1925 combines signals received from the FFTs 1920.1to 1920.P for each carrier frequency ƒ_(n) to generate at least onesignal corresponding to each carrier frequency ƒ_(n). The frequencycombiner 1925 processes the receive signals to provide any combinationof receiver performance and frequency reuse. The frequency combiner 1925may generate a plurality of subchannels for each frequency wherein eachfrequency sub-channel corresponds to a particular signal frequencytransmitted by a particular transmitter.

The CI combiner 1929 processes the multi-frequency signals produced bythe frequency combiner 1925 to separate interfering data signals on eachfrequency sub-channel. The CI combiner 1929 may perform any necessaryde-interleaving to compensate for data symbols spread over multiplediversity parameters.

The frequency combiner 1925 and the CI combiner 1929 may be providedwith adaptive weights from a weight generator 1924. The weights may begenerated with respect to a known training sequence and/or estimates ofthe received data symbols. For example, a plurality of decoders 1928.1to 1928.K decode the data signals received from the CI combiner 1929 togenerate a plurality of data-symbol estimates. These estimates, as wellas confidence measurements, may be used to generate hard or softdecisions from which weights are generated. The process of decoding mayinclude adaptive weighting and/or iterative processing. Decoding mayinclude error-detection coding, error-correction decoding,demultiplexing, despreading, compensation for channel distortions,decryption, etc. The decoders 1928.1 to 1928.K and/or the weightgenerator 1924 may include a parameter estimator (not shown).

The combiner 1929 may discard signals having one or more frequencies,signals in one or more subspaces, and/or signals from one or moreantennas 1920.1 to 1920.P. For example, one or more received signals maybe discarded to reduce the effects of noise and/or interference. Thecombiner 1929 and/or the decoders 1928.1 to 1928.K may include adecision processor (not shown) adapted to evaluate signalcharacteristics (e.g., power, SNR, SNIR, BER, interference level,channel distortion, etc.) in order to determine which signal(s) todiscard. The decision processor (not shown) may update its determinationof which signal(s) to discard relative to measured signalcharacteristics and/or one or more predetermined time intervals.

The decision processor (not shown) may provide a feedback signal to oneor more remote transmitters from which signals are received. Thefeedback signal may include a performance indication of the receivedsignals, channel estimates, and/or a known training sequence that allowsthe remote transmitter(s) to evaluate the channel. The feedback signalmay be provided with control information to adjust or suggestadjustments to signal-transmission characteristics (e.g., signal power,CI carrier frequencies ƒ_(n), frequency offset ƒ₀, frequency spacingƒ_(s), number of CI carriers, pulse overlap, beam pattern, spatial gaindistribution, signal polarizations, signal phases, interleaving, channelcoding, etc.) to compensate for fading, inter-symbol interference,co-channel interference, jamming, etc. These types oftransmission-signal adjustments may be made to perform power control,frequency-band adjustments (e.g., bandwidth exchange), link priority,multiplexing, multiple access, link security, throughput adjustments,adaptability to information type (e.g., voice or data), and ensurequality of service.

A diversity combiner (e.g., an MMSE diversity combiner) is used fordiversity reception in various systems, such as an adaptive antennaarray or a CI receiver. Diversity reception typically reduces oreliminates deep fades caused by multipath phase cancellations (i.e.,multipath fading). Diversity combining also produces gain (relative todiversity switching or non-diverse reception) by effectively combiningthe power of multiple received signals. Diversity combining may beemployed to optimize the quality of desired signals that are separatedfrom interfering signals. The SNR (and/or the signal-to-interferenceratio) may be maximized in interferometry processes, such as CI and/orarray processing. When CI is used with antenna arrays, array and CIdiversity combiners may be combined into a single diversity combiner.

FIG. 19B is a basic block diagram of a CI-based receiver having similarsystem components as those indicated by the same numbering in FIG. 19A.However, the receiver shown in FIG. 19B includes a combiner 1927 thatdoes not have differentiated subsystems, such as the frequency combiner1925 and the CI combiner 1929 shown in FIG. 19A. Rather, the combiner1927 is implemented as a combination of the frequency combiner 1925 andthe CI combiner 1929. Since array processing and CI combining processescan be similar, it is advantageous to combine these processes for someapplications.

FIG. 19C is a functional illustration of one possible embodiment of thecombiner 1927 shown in FIG. 19A. Each FFT 1920.1 to 1920.P separates aninput signal from an array element 1916.1 to 1916.P into a plurality offrequency components ƒ₁ to ƒ_(n). For example, the signals produced byFFT 1920.1 include {x₁(ƒ₁) to x₁(ƒ_(n))}. Signals produced by FFT 1920.Pinclude {x_(p)(ƒ₁) to x_(p)(ƒ_(n))}.

The frequency combiner 1925 includes a plurality of frequency-subspacecombiners 1925.11 to 1925.NK. Combiner 1925.11 generates afrequency-subspace signal y(ƒ₁,1) corresponding to frequency ƒ₁ inspatial sub-channel 1. Combiner 1925.N1 generates a frequency-subspacesignal y(ƒ_(N),1) corresponding to frequency ƒ_(N) in spatialsub-channel 1. In this particular embodiment of the invention, all ofthe frequency-subspace signals {y(ƒ₁,1) . . . y(ƒ_(N),1)} correspondingto spatial sub-channel 1 are processed in a subsystem 1929.1 of the CIcombiner 1929 to produce a CI signal y(k=1). Similarly, a CI signaly(k=K) is generated by a subsystem 1929.K from a plurality of the K^(th)spatial sub-channel's signals {y(ƒ₁, K) . . . y(ƒ_(N), K)} produced byfrequency-subspace combiners 1925.1K to 1925.NK. In other embodiments,CI signal components may be distributed across multiple spatialsub-channels, time intervals, and/or other diversity-parameter values.

The frequency-subspace combiners 1925.11 to 1925.NK are provided withcomplex weights w(ƒ_(n),k) to help separate interfering signals intospatial sub-channels. Complex weights ω(ƒ_(n),k) are provided to the CIcombiner 1929 to enhance the generation of CI signals y(k). The weightsw(ƒ_(n),k) and ω(ƒ_(n),k) may be generated with respect to one or moreoptimal-combining techniques. MMSE, ORC, maximum likelihood, equal gain,and/or other combining techniques may be employed. An iterativeweighting process may be employed, such as a process that generates softdecisions and uses feedback. The weights may be generated viablind-adaptive processes.

FIG. 19D illustrates one possible apparatus and method embodiment of thecombiner 1927 shown in FIG. 19B. A plurality of optimal-combiningsystems 1927.11 to 1927.NK provide complex weights ω(ƒ_(n),k)w(ƒ_(n),k)to signals output by each FFT 1920.1 to 1920.P. The complex weightsω(ƒ_(n),k)w(ƒ_(n),k) optimize sub-channel generation, as well as CIcombining. In one possible variation of this embodiment, a weightedcarrier or a weighted signal value y(ƒ_(n),k) corresponding to aparticular carrier frequency and subspace is provided at eachoptimal-combining system 1927.11 to 1927.NK output. Values y(ƒ_(n),k)corresponding to a particular CI signal are combined (e.g., summed). Theresulting CI signal may be a CI-based coded signal, such as a CI/DS-CDMAcoded signal or a CI-coded signal having a CI-based architecture. Inthis case, components of a k^(th) CI signal correspond to a k^(th)subspace. However, CI signal components may be distributed over multiplesubspaces. Furthermore, CI signal components may be distributed overother diversity-parameter values, such as, but not limited to, timeintervals, polarizations (linear and/or circular), and modes.

FIG. 20 illustrates a system adapted to transmit CI subspace coded datasymbols into a multipath channel 99 and a receiver adapted to processand decode the CI subspace coded data symbols. One or more data streamsare coupled into the transmitter via one or more data sources 1900.1 to1900.n. Each data stream is encoded with a code (e.g., a CI code or aCI/DS-CDMA code) by at least one coding system 1911.1 to 1911.n. Eachcoding system 1911.1 to 1911.n is coupled to a plurality N oftransmitter elements 1910.1 to 1910.N that couple the coded data intothe communication channel 99.

A plurality P of receiver elements 1916.1 to 1916.P are responsive tothe transmitted coded data symbols to provide a plurality of receivedsignals to a sub-space processor 1925. The sub-space processor 1925processes the received signals into separate sub-space signals.Sub-space processing may include blind-adaptive processing and/or mayuse known training sequences to generate and/or optimizesubspace-processing weights. Various combining techniques, such as, butnot limited to, MMSE, EGC, ORC, or maximum-likelihood combining, may beused.

Each subspace value generated by the sub-space processor 1925 mayinclude one or more coded data symbols. The sub-space values areprocessed in a symbol decoder 1928 that may be integrated with thesub-space processor 1925. The decoder 1928 decodes the coded datasymbols. The decoder 1928 may generate a reference code for a matchedfilter. The decoder 1928 may adjust one or more signal parameters (e.g.,phase, amplitude, etc.) of the coded data symbols with respect to areference code. The decoder 1928 may combine the coded data symbols toseparate at least one desired symbol from at least one interferingsymbol. Thus, various combining techniques may be employed. The decoder1928 may include a de-interleaver, a decision system, and/or a feedbackloop to perform iterative decoding. Data-symbol estimates generated bythe decoder 1928 may optionally be processed by a data processor 1930.

The transmitted signal x_(n)(t) due to an n^(th) user can be expressedby:

${x_{n}(t)} = {\sum\limits_{i = 1}^{B}{{b_{n}(i)}{s_{n}\left( {t - {iT}} \right)}}}$

where b_(n)(i) is an i^(th) coded data symbol, s_(n)(t) is acorresponding signaling waveform. The channel impulse response of then^(th) user is expressed by:

${h_{n}(t)} = {\sum\limits_{l = 1}^{L}{a_{nl}g_{nl}{\delta \left( {t - {i\; \tau_{nl}}} \right)}}}$

where a_(nl) is the array response, g_(nl) is the path gain, and τ_(nl)is the path delay.

A signal received by one of the receiver elements 1916.P is expressedby:

${r_{p}(t)} = {{\sum\limits_{n^{\prime} = 1}^{n}{{x_{n^{\prime}}(t)}{h_{n^{\prime}}(t)}}} + {\sigma \; {n(t)}}}$

where n(t) is a noise term. If the received signal r_(p)(t) is processedby a space-time matched-filter receiver, the receiver output y_(n)(i) isexpressed by:

${y_{n}(i)} = {\sum\limits_{l = 1}^{L}{g_{nl}^{*}a_{nl}^{H}{\int_{- \infty}^{\infty}{{r(t)}{s_{n}\left( {t - {iT} - \tau_{nl}} \right)}\delta \; t}}}}$

FIG. 21A illustrates an embodiment of a space-time matched-filterreceiver of the present invention. A plurality P of received signalsr₁(i) to r_(P)(i) are coupled to a set of demodulators 2016.1 to 2016.Pthat remove the signaling waveforms s_(n)(t). A plurality P of matchedfilters 2020.1 to 2020.P compensate for the space-time effects of thechannel 99. Signals corresponding to at least one space-time subspaceare combined to generate at least one received coded data symboly_(n)(t). For example, the coded data symbols y_(n)(t) may includeCI-coded symbols and/or CI-based coded data symbols. A symbol decoder2028 processes the coded data symbol y_(n)(t) to generate at least onedata-symbol estimate.

FIG. 21B illustrates an embodiment of a space-frequency matched-filterreceiver of the present invention. A plurality P of matched filters2020.1 to 2020.P compensate for the space-frequency effects of thechannel 99. Signals corresponding to at least one space-frequencysubspace are combined to generate at least one received coded datasymbol y_(n)(t).

Since CI-based signals can be processed by time-domain andfrequency-domain receivers, in some cases it can be advantageous toprocess received signals in both the time domain and the frequencydomain. Thus, received CI signals may be processed by separatetime-domain and frequency-domain receivers. Alternatively, received CIsignals may be processed by a combined time-domain and frequency-domainreceiver.

FIG. 21C illustrates a space-time receiver of the present invention. Aplurality of transmitted signals are received and processed by thereceiver. The plurality of transmitted signals are coded to carry atleast one data stream. Each symbol of a particular data stream is spreadover the plurality of transmitted signals. For example, spreading may beperformed via CI codes and/or CI/DS-CDMA codes.

The received signals r₁(i) to r_(P)(i), such as signals received fromspatially separated transmitters, have different delay profiles. In amultipath environment, multiple replicas of the transmitted signals arereceived at different times. The received signals r₁(i) to r_(P)(i) arecoupled to a set of demodulators 2016.1 to 2016.P that remove thesignaling waveforms s_(n)(t).

A reference-code generator 2028 is coupled to a plurality P of matchedfilters 2020.1 to 2020.P that compensate for the space-time effects ofthe channel 99. The combination of applying codes to the filters 2020.1to 2020.P and combining the filtered signals decodes the coded symbols.A j^(th) user's code provides an i^(th) matched filter with thefollowing filter function:

h′ _(i) ⁻¹(t)=c* _(jp)(t)h _(i) ⁻¹(t)

where c*_(jp) (t) represents a p^(th) complex-conjugate chip of a j^(th)user's code. Preferably, the filter-function term, h′_(i) ⁻¹ (t), isadapted to minimize the effects of noise and/or interference. Codesand/or the filter function, h₁ ⁻¹ (t) may be adjusted to compensate forchannel distortion. If the code is a CI code, the system may be designedwithout code-length constraints. For example, orthogonal CI code lengthsmay be adapted to a given number of transceiver elements or subset oftransceiver elements, whereas Walsh codes are constrained to codelengths of powers of two.

FIG. 21D illustrates a space-frequency receiver of the presentinvention. A plurality of transmitted signals r(t) are received andprocessed by the receiver. The plurality of transmitted signals arecoded to carry at least one data stream. In one form of space-frequencycoding, each symbol of a particular data stream is spread over aplurality of same-frequency transmissions. A particular informationsignal may be provided with (e.g., modulated by) a code bit associatedwith each antenna that transmits the signal. In another form ofspace-frequency coding, an information signal is transmitted on multiplecarrier frequencies in addition to multiple antennas. Other forms andvariants of space-frequency coding may be performed. In any of thesecases, it is preferred that spreading be performed via CI codes and/orCI/DS-CDMA codes.

FIG. 21E shows a generalized illustration of a multi-element receiver ofthe present invention. A plurality of interfering transmitted signalsr(t) are received and processed by a spatial demultiplexer 2016, whichseparates a plurality of desired signals y′₁(t) to y′_(P)(t) from one ormore interfering signals. A symbol decoder 2028 processes the signalsy′₁(t) to y′_(P)(t) with respect to code chips c_(jp) generated by adecode-weight generator 2026. The desired signals y′₁(t) to y′_(P)(t)are weighted and combined with respect to some predetermined combiningprocess, such as MMSE, EGC, ORC, and/or maximum-likelihood combining togenerate a data-symbol stream y_(i)(t). Channel compensation may beintegrated into demultiplexing and/or decoding.

FIG. 21F shows an alternate embodiment of a multi-element receiver ofthe present invention. A spatial demultiplexer 2017 receives a pluralityof interfering transmitted signals r(t) from a communication channel(not shown) and a plurality of code chips c_(jp) generated by adecode-weight generator 2026. The received signals r(t) are weighted andcombined to reduce interference from interfering spatial subchannelsand/or perform decoding. It is preferable that decoding and codingoperations be performed via CI codes and/or CI/DS-CDMA codes.

FIG. 21G is a functional illustration of a multi-element receiver of thepresent invention. Symbols and indices used in the description of thisembodiment do not necessarily correspond to the same symbols usedelsewhere in the specification.

A plurality k of receiver elements 2016.1 to 2016.k provide signalsd₁(t) to d_(k)(t) (illustrated by a received signal set 2051). Abreakdown 2052 of the received signals d₁(t) to d_(k)(t) illustrates alinear combination of transmitted information signals s_(j)(t) (=1 to k)scaled by complex channel parameters α_(jk) indicative of channeldistortion, such as multipath fading, inter-symbol interference, pathloss, etc. Noise, although not shown, may be considered to be present inthe breakdown 2052 of received signals. The number of transmittedsignals s_(j)(t) in each received signal d_(k)(t) is preferably lessthan or equal to the number of received signals d_(k)(t) (e.g., numberof receiver elements) having algebraically unique combinations of theunknown transmitted signals s_(j)(t).

A code generator 2027 and a subspace-weight generator 2029 provide ak′Xk matrix of weights applied to at least one set of received signalsd₁(t) to d_(k)(t). The value k′ represents the number of unknowntransmitted signals s_(j)(t), which may be less than or equal to thenumber k of received signals d₁(t) to d_(k)(t). The code generator 2027provides at least one complex code, such as a j^(th) code Σc_(jk). Thesubspace-weight generator 2029 provides sub-space weights β that areused to reduce interference between received samples of the transmittedsignals s_(j)(t). The result of applying the sub-space weights β is thatthe interfering spatial channels are substantially separated. Theseparated spatial sub-channels are indicated by sub-channel terms y₁(t)to y_(k)(t) in a dot-product representation 2055 of the signals d₁(t) tod_(k)(t) with the k′Xk weight matrix. The terms y₁(t) to y_(k)(t) arerepresented by a decomposition 2056.

The decomposition 2056 illustrates that a plurality of coded datasymbols are present in each subchannel. In fact, after sub-channelprocessing, each sub-channel term y_(k)(t) is represented by a linearcombination of transmitted signals s_(j)(t). Thus, the multiplication ofeach term y₁(t) to y_(k)(t) by a j^(th) code, c_(j1) to c_(jk), and asubsequent summation process 2057 provides an estimate r_(j)(t) of thej^(th) transmitted signal s_(j)(t). Various optimization techniques,including iterative soft-decision techniques, may be employed to reducethe effects of noise and/or interference.

FIG. 22 illustrates a receiver array processor that provides anadditional dimension to coding. A plurality P of receiver elements2016.1 to 2016.P receive coded transmissions to generate receivedsignals r₁(t) to r_(P)(t). The received signals r₁(t) to r_(P)(t) areprocessed in a plurality of filter banks 2040.11 to 2040.PK. The filterbanks 2040.11 to 2040.PK and/or the receiver elements 2016.1 to 2016.Pmay provide conversion to baseband and/or intermediate frequencies. Forexample, received signal r₁(t) is processed by K sets of filters 2040.11to 2040.1K, where K is the number of data channels to be separated. Eachfilter (such as filter 2040.11) may be a time domain matched filterexpressed by a plurality L of delay taps. Digital filters, such aspolyphase filters, adapted to perform down sampling may be adapted toperform up sampling.

Filtered signals from different receiver elements 2016.1 to 2016.P foreach of the K data symbols are optionally weighted with complex weights205.111 to 205.PKL. Applied weight values a_(pkl) correspond to at leastone of receiver element p, data symbol k, and path l. The weightedsignals are combined with summing circuits 2042.1 to 2042.K. Thecombined signals may optionally be weighted 206.111 to 206.P1L andcombined 2045 to produce a vector estimate y₁(t) to y_(K)(t) of thetransmitted data vector. Coding may be integrated into weights g₁₁ tog_(PL) and/or weights a₁₁₁ to a_(PKL).

The vector estimate y₁(t) to y_(K)(t) is optionally processed by adecoder 2028. The decoder 2028 may decode data symbols that are encodedvia one or more codes, such as, but not limited to, multiple-access,channel, spreading, encryption, and error-correction codes. Preferably,the codes are CI and/or CI-based codes. Either or both code chips andweights may be adjusted with respect to channel estimation. Code and/orweight adjustments may be made with respect to some optimizationprocess. For example, codes and/or weights may be adjusted to optimizesome measurement, such as signal power, SNR, SNIR, etc.

FIG. 23A illustrates one of many possible CI/DS-CDMA signal structures.A repetitive CI pulse structure (such as a CI pulse structurecharacterized by uniformly spaced carriers) is provided with coding thatgenerates a direct-sequence-like time-domain structure. Polyphase codesmay be applied to individual carriers to produce a direct-sequencestructure. Alternatively, direct-sequence codes may be applied to thetime-domain pulses to produce a direct-sequence structure.

A repetitive direct-sequence code C₁={c₁, c₂, . . . , c_(N)} is providedwith data symbols d₁, d₂, . . . , d_(m). In this case, overlappingpseudo-orthogonal pulses are provided with DS-CDMA codes. The number ofcarriers is N/2 and the repetition rate is related to the inverse of thecarrier spacing ƒ_(s). The pulses, as well as the direct-sequenceperiods may overlap.

One or more transmitter elements may transmit the signal illustrated byFIG. 23A. Each of a plurality of transmitter elements may transmit aseparate signal component, such as a pulse or a carrier frequency. Phasesweeping may be applied to one or more transmitter elements to achievespatial-diversity benefits in addition to directionality.

FIG. 23B illustrates signal structures of one set of embodiments of amulti-dimensional CI/DS-CDMA method and apparatus of the invention. Aplurality k of coded data streams are used to convey one or more streamsof data symbols d_(mfk). For example, an m^(th) data bit d_(mf1) of afirst (k=1) coded data stream is provided with an m^(th) N-chip codeC_(mf1)={c_(1mf1), c_(2mf1), . . . , c_(Nmf1)}, where f is somediversity-parameter space.

Codes C_(mjk) may differ for different values of m, f, and/or k. Similarcodes may be used for different data symbols d_(mfk) if it is possibleto differentiate between codes due to one or more diversity-parametervalues. Multiple diversity-parameter values may be impressed with one ormore coded data streams. Multiple diversity-parameter values may bemodulated with multiple coded data streams. The interfering data symbolsmay be separated via any combination of sub-space processing anddecoding.

FIG. 24 illustrates a signal structure derived from an alternate set ofapparatus and method embodiments of the invention. A first-layerdirect-sequence code C₁={c₁, c₂, . . . , c_(N)} (which may be aCI/DS-CDMA and/or CI code) is provided as a carrier for coded datasequences. For example, an m^(th) data bit d_(m) is impressed onto asecond-layer code CC₁={cc₁, cc₂, . . . , cc_(N′)} having a duration of aplurality of first-layer code C₁ periods. In this case, each code bitcc_(mN′) spans one period of the first-layer direct-sequence code C₁.Data symbols and data streams can be separated via differences in eitherthe first-layer-layer code C₁ or the second-layer code CC₁.

Although transceiver arrays are typically regarded as spatially diverseantenna arrays, any diversity parameter may be used to characterize atransceiver array. The importance of transceiver arrays with respect tomany aspects of this invention is particularly directed to the sub-spaceprocessing. CI signals may include any sub-space bases as carriers. CIsignals may be encoded via sub-space processing and/or spread acrossmultiple sub-space bases.

Sub-space bases, as used herein, refers to any overlapping set ofdiversity parameters that are processed, such as via interferometry, toproduce independent, substantially orthogonal sub-channels aregenerated. Some sub-space bases include spatial sub-spaces, directionalsub-spaces, polarization sub-spaces, temporal sub-spaces, phasesub-spaces, quasi-orthogonal code sub-spaces, quasi-orthogonal waveletsub-spaces, frequency-band subspaces, CI phase-space subspaces, and anycombination of the above-mentioned subspaces.

In-phase and quadrature-phase subspaces may be established, such as viaa pair of orthogonal diversity parameters (e.g., perpendicularpolarizations, a phase offset of 90 degrees between two signals,orthogonal frequencies, orthogonal codes, orthogonal time intervals,etc.). In-phase and quadrature-phase subspaces may be designated as apair of orthogonal subspaces. One subspace is used to convey a signalmagnitude related to magnitude of an in-phase component and a secondsubspace is used to convey a signal magnitude representing aquadrature-phase signal magnitude.

FIG. 25A illustrates a basic subspace processing method of the presentinvention. A data-sequence vector u having length N is provided to atransmit filter 2501 before being coupled into a communication channel99. The channel acts on a transmitted data vector x via an N×Nnon-singular matrix H and an additive noise vector n having a varianceof N₀/2. A signal vector y received from the channel 99 is expressed by:

y=Hx+n

The received signal vector y is processed by a matched filter 2502 togenerate an output signal vector z, which is expressed by:

z=R _(f) x+n′

where R_(f)=H*H and n′=H*n. An estimate of x given z is expressed by:

x=R _(b) z+e

where R_(h) ⁻¹=R_(f)+(N₀/2)R_(xx) ⁻¹, R_(xx) is the covariance of x, ande is the MMSE error.

Additional processing, such as any of various adaptive feedbacktechniques, may be incorporated at the receiver end.

Although sub-space processing is commonly associated with arrayprocessing, the methods of the present invention may incorporatedecoding into sub-space processing techniques. In one set ofembodiments, sub-space processing and CI combining methods are combined.Sub-space processing may include frequency-diversity interferometryand/or interferometry between one or more sets of diversity-parametervalues including, but not limited to, polarizations, codes, modes,phases, and delays.

FIG. 25B illustrates a subspace processing method of the presentinvention that employs decision feedback. In this case, Choleskyfactorization provides:

R _(f) =G*S ₀ G

where S₀ is a diagonal matrix and G is a monic, upper-diagonal matrix. Adecision feedback equalizer includes a feed-forward filter 2503, adecision system 2504, and a feedback filter 2505. A decision feedbackequalization algorithm that may be used in conjunction with theinvention is represented by:

$\overset{\sim}{z}:={S_{o}^{- 1}G^{- *}H^{*}y}$ for  k = 0, N − 1${\hat{x}}_{N - k}:={{decision}\left( {{\overset{\sim}{z}}_{N - k} - {\sum\limits_{i = 1}^{k}{g_{{N - k},{N - k + i}}{\hat{x}}_{N - k + i}}}} \right)}$end

where g_(ij) are elements of G and {circumflex over (x)}_(i) and{circumflex over (z)}_(i) are elements of {circumflex over (x)} and{circumflex over (z)}, respectively.

A decision feedback equalizer may reorder the received substreams byrearranging the rows and columns of H. For example, a layered processingapproach may be employed. Symbols are detected sequentially andinterference from previously detected symbols is subtracted. Receivedvector elements are weighted to null (or reduce) interference fromundetected symbols.

CI/DS-CDMA Frequency Agility

CI-based signals can mimic the bandwidth characteristics of conventionalprotocols, such as TDMA (e.g., GSM) and DS-CDMA protocols. Adjacentoverlapping CI carriers appear as a continuous spectrum over thebandwidth of the conventional protocol. However, frequency-diversitybenefits diminish as the coherence bandwidth of the channel increases.

FIG. 26A is a frequency-domain plot of an alternative CI-based protocoland FIG. 26B is a frequency-domain plot of an associated conventionalprotocol. For example, the CI-based protocol may be CI/DS-CDMA and theconventional protocol may be DS-CDMA. The CI/DS-CDMA signal has the sametotal bandwidth as the conventional signal. However, the CI carriersthat characterize the CI-based protocol are distributed non-continuouslythroughout a given frequency band.

The CI carriers may be predetermined or dynamically chosen to enhancefrequency-diversity benefits, compensate for channel distortions, avoidinterference, ensure quality of service, adapt to different linkpriorities, provide for changing data rates, accommodate coding, and/orprovide multiple access. The CI carriers may be grouped with respect toavailable, but not necessarily continuous, frequency bands. The CIcarriers may be selected dynamically with respect to changing frequencyallocations, different applications, changes in throughput, changingsystem requirements, different numbers of users, etc.

CI carriers may be selected or adjusted to affect various controlprocedures, such as, but not limited to, power control, carrier senseprocedures, authentication, identification, validation, switching,routing, encryption key transmission, and/or conveying control signals.One or more CI carriers may be adjusted with respect to amplitude,frequency, and/or phase. Other diversity parameters, such aspolarization, directionality, etc. may be adjusted.

FIG. 27 illustrates carrier placements for multiple CI channels thatsimultaneously benefit from frequency diversity of nearly the entirefrequency band. Frequency profiles of the CI carriers are arranged suchthat adjacent carriers correspond to different channels. However,frequency components associated with each channel are preferablypositioned throughout a relatively wide frequency band. In one set ofembodiments, the aggregate bandwidth of the CI frequency componentsequals the bandwidth of a corresponding conventional single-carriersignal. Although the aggregate signal bandwidth of the CI-based signalis identical to the bandwidth of the conventional signal, the CI-basedsignal enables wideband-like frequency diversity benefits.

Variations to carrier spacing and distributions of each user's signalsmay be made without departing from the scope of the present invention.For example, the carriers of one or more users may overlap. The numberof users may be less than or greater than the number of carriers. Therelative frequency-domain positioning of users' signals may be changedwith respect to time. Carrier frequencies may be positioned uniformly ornon-uniformly. Users may simultaneously share one or more carrierfrequencies. Carrier frequencies may be selected and/or adjusted withrespect to channel conditions, such as interference, distortion, andjamming. Predistortion may be applied to the carriers. Carriers havingparticular frequencies may be amplified, attenuated, and/or avoided withrespect to channel conditions that affect carrier reception or thatcause the carriers to impact the performance of some other system.

FIG. 28A illustrates a set of methods for generating CI-based signals.Since CI is a multicarrier-based signal architecture, a step ofproviding for carrier generation 2801 may precede or follow at least onetime-domain shaping step 2802. Alternatively, carrier generation 2801and time-domain shaping 2802 may be combined. A multicarrier signalhaving a predetermined time-domain profile may be coupled 2803 into acommunication channel.

Carrier generation 2801 may include providing for a CI-basedmulticarrier architecture. For example, carrier generation 2801 mayinclude any method of transforming frequency-domain data symbols intoone or more time-domain signals characterized by a multicarrierarchitecture. Various transformation techniques may be used, including,but not limited to Fourier transforms, wavelet transforms, and Walshtransforms. Various permutations and methods of performing thesetransforms may be incorporated into the carrier generation step 2801.

Carrier generation 2801 may include the generation of harmonic ornon-harmonic carriers. For example, a pulse generator or some otherharmonic source may be employed to generate signals having asubstantially uniform frequency spacing. A plurality of localoscillators or other signal-generation systems may be coupled togetherto provide carrier generation. Non-linear devices may be used togenerate harmonically rich signals. Various methods involving crosscoupling, interferometry, feedback, and/or mode locking may be used togenerate multicarrier signals. Alternatively, a wave look-up table mayprovide an integral part of a carrier-generation step 2801.

Time-domain shaping 2802 may include any combination of pre-processingand post-processing relative to carrier generation 2801 that helps shapethe time-domain characteristics of a superposition of carriers. Shaping2802 may be performed via selection of frequency-bin values in a Fouriertransform operation. Consequently, time-domain shaping 2802 may includecalculating frequency-bin values. Typically, time-domain shapingincludes impressing data symbols onto the carriers. However, datamodulation may be performed in the carrier-generation step 2801.

Alternatively, CI codes may be generated without physically generatingcarriers. Since CI codes are based on relations between carriers, thecarrier-generation step 2801 may simply provide one or more basic CIcodes. Carrier generation 2801 may include calculating or retrievingcomplex variations of simple CI codes. Time-domain shaping 2802 mayprovide data modulation or any other form of signal shaping prior tocoupling 2803.

The coupling step 2803 may perform any necessary signal processing tofacilitate conveyance by a communication channel. For example, thecoupling step 2803 may include filtering, amplification, up-conversion,modulation, etc.

FIG. 28B illustrates a set of methods for receiving one or more CI-basedsignals. CI signals are coupled 2804 out of a communication channel andprocessed in a frequency-domain combining step 2805. Signals produced byfrequency combining are optionally passed to a data-processing step2806.

The coupling step 2804 may include any of various signal-processingsteps (not shown) required to convey a received signal into at least oneintermediate-frequency or baseband signal. The combining step 2805 mayseparate received signals into carrier-signal components and providecomplex weights to the signal components prior to combining. Variouscombining techniques may be used, including, but not limited to MMSE,maximum likelihood combining, EGC, zero forcing, etc. The combining step2805 may employ iterative feedback techniques and/or equalizationtechniques.

Data processing 2806 may be performed on signals output from thecombining step 2805. Various data processing techniques that may beemployed include, but are not limited to, demodulation, decoding, symbolestimation, correlation, etc.

Alternatively, the combining step 2804, when performed on a CI-codedsignal, may include decoding. For example, combining 2804 may includematched filtering, coherence multiplexing, and/or some complementarysignal processing (e.g., phase shifting) provided to the received signalrelative to some received or locally generated reference signal.

Performance Overview of CI-Based Protocols

CI provides substantial improvements in throughput, power efficiency,and signal quality while maintaining the time-domain characteristics ofvarious multiple-access protocols. Published performance improvements ofCI with various conventional multiple-access protocols are summarized asfollows:

In MC-CDMA, CI coding enables a seamless transition between orthogonaland quasi-orthogonal coding. CI codes are capable of supporting twice asmany users, doubling network capacity without performance degradation.

In TDMA, CI coding provides over 10 dB performance gain at probabilityof errors of 10⁻³. CI-TDMA with 2N symbols per burst still outperformstradition TDMA (with the usual N symbols per burst and using a DFEequalizer) by up to 7 dB at a probability of error of 10⁻³.

In DS-CDMA, CI provides a 14 dB performance improvement at probabilityof errors of 10⁻². Furthermore, CI applied to DS-CDMA can double thecapacity of DS-CDMA while maintaining performance improvements.

CI-OFDM provides a 10 dB performance benefit over OFDM at a probabilityof error of 10⁻³. CI-OFDM can trade off some of its performance benefitfor significant gains in the throughput of OFDM systems. Coded CI-OFDMoffers the same throughput as ideal OFDM with the performance ofconventional coded OFDM. Furthermore, CI-OFDM eliminates problems ofhigh PAPR.

CI Codes Basic CI Codes

CI codes, as used herein, may include basic CI codes or advanced CIcodes. CI codes are based on mathematical relationships between CIcarriers and phase spaces. CI codes can be used as direct-sequencecodes, multicarrier codes (e.g., MC-CDMA), etc. Applications of CI codescan be extended to any application of conventional binary directsequences, including but not limited to, spread spectrum, multipleaccess, channel coding, encryption, anti jamming, etc. CI codes may beapplied across any set of orthogonal or quasi-orthogonaldiversity-parameter values or subspaces. Although CI codes can berepresented with respect to phase relationships generated by vectorprecession in the complex plane, the implementation of CI coding can beextended to circular, elliptical, and linear polarizations.

In one set of embodiments of the invention, basic CI polarization codesmay be based on vector precession in a two- or three-dimensionalpolarization plane. Advanced CI codes may be based on basic CIpolarization codes. Similarly, vector rotation in a plane orhigher-dimension field of other orthogonal bases may be used to generatebasic and/or advanced CI codes. The basic family of CI codes (alsoreferred to as basic CI codes) can be generated from an M×M matrix ofelements having phases φ_(mn) described by:

φ_(mn)=2πmn/M+2πƒ₀ m/ƒ _(s) M,

where m and n are row and column indices, respectively. M may have anypositive integer value. The second term in φ_(mn) is an optional phaseshift applied to all terms in a row. The phase-shift value correspondsto a carrier frequency offset ƒ₀ and a sub-carrier separation ƒ_(s). Abasic CI code c_(m) can be a row or column vector consisting of terms:

$c_{m} = {^{\; m\; \varphi^{\prime}}{\sum\limits_{n = 0}^{N - 1}{^{\; m\; n\; \varphi}\hat{n}}}}$

where φ=2π/M and φ′=2πƒ₀/ƒ_(s)M.

Some of the CI codes are complex-conjugate pairs. For example,correlations between CI codes are expressed by the followingrelationship:

${corr}_{m,m^{\prime}} = {\left( \frac{1}{M} \right)^{{{({m + m^{\prime}})}}\varphi^{\prime}}{\sum\limits_{n = o}^{M - 1}^{\; {n{({m + m^{\prime}})}}\varphi}}}$

The correlations are non-zero for (m+m′)=M.

CI codes may have polyphase and/or multi-magnitude values. A CI code setmay include one or more binary code vectors corresponding to at leastone conventional binary-phase code. In the case where CI codes includecomplex-valued chips, the real and imaginary values may be impressedupon different orthogonal parameters. For example, a magnitudecorresponding to a real value may be modulated onto an in-phase carriercomponent whereas a corresponding imaginary value may be modulated ontoa quadrature-phase carrier component. Orthogonal components may include,but are not limited to, perpendicular linear polarizations, left-handand right-hand circular or elliptical polarizations, orthogonalpolarization spins, subspaces (e.g., spatial, directional, temporal,phase, polarization, etc.), orthogonal frequencies, orthogonal timeintervals, direct-sequence codes, etc. Modulation may include one ormore of any modulation type, such as phase modulation, amplitudemodulation, frequency modulation, polarization modulation, etc.

Phase shifts corresponding to CI code chips may be impressed upon asingle carrier or onto multiple carriers. In one embodiment, phaseshifts are impressed relative to a transmitted or locally generatedreference phase. In another embodiment, differential phase modulation(DPM) is employed. In one embodiment, DPM may be employed on a singlecarrier. In another embodiment, DPM is applied to a multicarriertransmission protocol. In one embodiment, each phase shift is conveyedas a phase differential between at least two carriers.

CI codes may be applied to ordinary direct-sequence (e.g., DSSS orDS-CDMA), MC-CDMA, OFDM, coded OFDM, Discreet Multitone, WavelengthDivision Multiplexing (WDM), ultra-dense WDM, Multi-tone CDMA, DiscreetWavelet Multitone, Multi-code spread spectrum (such as described in U.S.Pat. No. 6,192,068), or any of the Carrier Interferometry protocols(such as described in Applicant's papers, patents, and patentapplications that are incorporated by reference). In the case where CIcodes are utilized in a multicarrier transmission protocol, phase-shiftcoding may be accomplished in any of several ways. Each carrier may bephase shifted with respect to each chip of a CI code chip sequence. Eachcarrier may be modulated with respect to any single-carrier modulationscheme. Each carrier may be modulated with one or more subcarriers thatare encoded with CI code chips. Each carrier may be provided with atleast two diversity parameters that are modulated to convey real andimaginary parts of the CI code chips.

Multicarrier signals may be defined by any set of substantiallyorthogonal diversity-parameter values. These diversity parameters mayinclude, without limitation, frequency, phase space, polarization(including linear, circular, elliptical) in two or three dimensions,mode, code (e.g., DS and/or CI), time, any type of subspace, and anycombination of diversity parameters.

The basic CI codes can be combined (with each other or with otherdirect-sequence codes) to form other families of polyphase and/orpoly-magnitude CI codes. In any set of CI codes, the chip sequences maybe truncated, appended, rearranged, concatenated, etc., to generateorthogonal or quasi-orthogonal chip sequences. Codes of similar ordifferent lengths may be concatenated. Different chip sequences may becombined in such a way that at least one chip sequence is interleavedwith chips from at least one other code.

CI code vectors may be multiplied by other code vectors, including, butnot limited to, direct-sequence codes, complementary codes, and/or otherCI codes. Groups of CI code chips may be modulated (scaled and/orshifted) with respect to other code chips. For example, a CI code may beoverlayed with a long code, a Hadamard-Walsh code, a Barker code, a Goldcode, a Kasami code, another CI code, or some other code. CI coding mayinclude multiple levels of coding wherein at least one set of code chipsmodulates at least one other set of code chips.

The basic CI codes of a particular length form an orthonormal basis. Neworthonormal bases can be generated by linearly combining CI codes of aparticular length. More advanced permutations of CI codes may also becombined to form orthonormal bases. The orthonormal bases may bemultiplied by code chips of other sequences, such as Hadamard-Walsh,Gold, CI, etc.

Data symbols may be mapped to CI codes to effect channel coding. For thepurpose of mapping, a set of CI codes may be doubled by including a codeset multiplied by the value −1 (e.g., bi-orthogonal codes). CI codes maybe used to generate trans-orthogonal (e.g., simplex) codes.Quasi-orthogonal mapping may be performed by phase shifting or scalingthe CI codes. A second set of orthogonal CI codes may be generated byrotating the phase of a first code set by π/2, thus providing in phaseand quadrature phase CI codes.

CI codes may be decoded in the same manner in which conventionaldirect-sequence or multicarrier codes are decoded. A received signal maybe correlated with a complex-conjugate code. The received signal may beprocessed with an FIR filter having coefficients set appropriately todecode a desired signal. The received signal may be sampled and summed.Optionally, samples of the received signal may be weighted prior tobeing summed to compensate for any of various factors, such as channeleffects, transmitter-side encoding (e.g., to reduce PAPR), jamming, etc.Weighting may be performed with respect to one or more optimizationprocesses in which weights are adjusted with respect to somemeasurement, such as SNR, BER, received signal power, etc.

The received signal may be phase shifted with respect to chip phases ofa decoding signal. If a received signal includes multiple samples perchip interval, the chip samples may be time shifted with respect to thechip phases of the decoding signal. In another embodiment, the samplescorresponding to each chip are cyclically shifted with respect to adecode chip sequence. Subsequent processing, such as sampling, adding,comparison, quantizing, and/or decision making (hard and/or soft) may beperformed to evaluate data symbols measured after the decoding process.

Advanced CI Codes

Advanced CI codes can involve one or more types of processing applied tobasic CI codes. Some examples of advanced CI codes illustrated hereininclude matrices resulting from processing basic CI codes with codevectors from a Hadamard-Walsh matrix, matrices resulting from vectorsderived from Hadamard-Walsh/CI matrices, and expanded CI matrices basedon Hadamard-Walsh matrix expansion. The term, advanced CI code, maydescribe many other forms, variations, and implementations of CI coding.

FIG. 29A shows a conventional 4×4 Hadamard-Walsh matrix HW_(4×4). Ann^(th) row of the matrix is an orthogonal Hadamard-Walsh code vectorHW_(4×4)(n). Each code vector HW_(4×4)(n) has zero cross correlationwith the other code vectors HW_(4×4)(n′≠n) and a non-zero correlationwith itself.

FIG. 29B shows a basic 4×4 CI matrix, CI_(4×4). An n^(th) row of the CImatrix CI_(4×4) denotes a CI code vector, CI_(4×4)(n). CI matrix (row xcolumn) sizes are not constrained to powers of two. Basic N×N CImatrices may be generated with any value of N.

FIG. 30A shows the 4×4 CI matrix CI_(4×4) multiplied by values of thefirst-row Hadamard-Walsh vector, HW_(4×4)(1). Each column value ofvector HW_(4×4)(1) multiplies a corresponding column of the CI matrixCI_(4×4). In this case, the vector HW_(4×4)(1) consists of all ones.Thus, the CI matrix CI_(4×4) multiplied by HW_(4×4)(1) produces theoriginal CI matrix, CI_(4×4).

FIG. 30B shows the 4×4 CI matrix CI_(4×4) multiplied by values of thesecond-row Hadamard-Walsh vector, HW_(4×4)(2). The row vectors in FIG.30B are the same as the row vectors in FIG. 30A, except that their orderin the matrix has been cyclically shifted by two positions.

FIG. 30C shows the 4×4 CI matrix CI_(4×4) multiplied by values of thethird Hadamard-Walsh row vector, HW_(4×4)(3). The first and third rowsof the matrix shown in FIG. 30C correspond to the third and fourth rowsof the 4×4 Hadamard-Walsh matrix shown in FIG. 29A. The second andfourth rows of the matrix shown in FIG. 30C are quaternary-phase vectorsthat do not correspond to either of the two quaternary-phase vectors inthe 4×4 CI matrix CI_(4×4) shown in FIG. 29B. The quaternary-phase codevectors shown in FIG. 29B and FIG. 30C form an orthogonal code set.

FIG. 30D shows the 4×4 CI matrix CI_(4×4) multiplied by values of thefourth Hadamard-Walsh row vector, HW_(4×4)(4). The row vectors in FIG.30D are the same as the row vectors shown in FIG. 30C, except that theirorder in the matrix has been cyclically shifted by two positions.

FIG. 31A illustrates a selection of the quaternary-phase vectors fromthe matrices shown in FIG. 30A and FIG. 30C. These vectors form a 4×4poly-phase code matrix PC_(4×4) shown in FIG. 31C. The vectorsPC_(4×4)(n) shown in FIG. 31C have zero autocorrelation and zerocross-correlation for code vectors that are not complex conjugates ofeach other. None of the CI code vectors in PC_(4×4) include an all-onesvector.

FIG. 31B illustrates a selection of binary-phase vectors from thematrices shown in FIG. 30A and FIG. 30C. These vectors are thecomponents of the basic Hadamard-Walsh matrix HW_(4×4) shown in FIG.29A.

FIG. 32A shows an 8×8 Hadamard-Walsh matrix HW_(8×8) generated from the4×4 Hadamard-Walsh matrix HW_(4×4) using the Hadamard-Walshmatrix-expansion technique. This technique uses a 2^(n−1)×2^(n−1) matrixA₂ _(n−1) _(×2) _(n−1) to generate a 2^(n)×2^(n) matrix A₂ _(n) _(×2)_(n) :

$A_{2^{n} \times \; 2^{n}} = \begin{bmatrix}A_{2^{n - 1} \times \; 2^{n - 1}} & A_{2^{n - 1} \times \; 2^{n - 1}} \\A_{2^{n - 1} \times \; 2^{n - 1}} & {- A_{2^{n - 1} \times \; 2^{n - 1}}}\end{bmatrix}$

where A is a matrix typically characterized by orthogonal code vectors.

FIG. 32B shows an 8×8 CI matrix PC4 _(8×8) generated from the 4×4polyphase CI matrix shown in FIG. 31C via the Hadamard-Walshmatrix-expansion technique. Each of the 8 code vectors is a quaternary8-chip code. The first and third vectors PC4 _(8×8)(1) and PC4 _(8×8)(3)are complex conjugates of each other. Other complex-conjugate pairsinclude vectors PC4 _(8×8)(2) and PC4 _(8×8)(4), PC4 _(8×8)(5) and PC4_(8×8)(7), and PC4 _(8×8)(6) and PC4 _(8×8)(8).

FIG. 32C shows an 8×8 CI matrix CI_(8×8) generated from a 4×4 CI matrixCI_(4×4) via the Hadamard-Walsh matrix-expansion technique. Although theHadamard-Walsh matrix expansion is designed to generate Hadamard-Walshcodes of length 2^(n), this matrix-expansion technique may be used togenerate CI codes from any N×N CI-code matrix. The code length N is notconstrained to be 2^(n).

The 8×8 CI matrix CI_(8×8) shown in FIG. 32C includes two binary-phase8-chip codes (which correspond to the first and second rows of the 8×8Hadamard-Walsh matrix HW_(8×8) shown in FIG. 32A), two quaternary-phasecode vectors (which correspond to the first and third rows shown in FIG.32B), and four octonary-phase code vectors including twocomplex-conjugate pairs CI_(8×8)(2) and CI_(8×8)(8), and CI_(8×8)(4) andCI_(8×8)(6).

FIG. 33A shows an 8×8 CI matrix HW_(8×8)(1)×CI_(8×8) resulting frommultiplication of the 8×8 CI matrix CI_(8×8) shown in FIG. 32C by thefirst row vector HW_(8×8)(1) of the 8×8 Hadamard-Walsh matrix, HW_(8×8),shown in FIG. 32A. Each value of vector HW_(8×8)(1) multiplies thecorresponding column of the CI matrix CI_(8×8). In this case, the vectorHW_(8×8)(1) consists of all ones. Thus, the CI matrixHW_(8×8)(1)×CI_(8×8) is identical to the CI matrix CI_(8×8). The CImatrix HW_(8×8)(1)×CI_(8×8) includes two binary-phase 8-chip codes,HW_(8×8)(1) and HW_(8×8)(2), two quaternary-phase code vectors, PC4_(8×8)(1) and PC4 _(8×8)(3), and two complementary octonary-phase codepairs, CI_(8×8)(1) and CI_(8×8)(1)*, and CI_(8×8)(2) and CI_(8×8)(2)*.

FIG. 33B shows an 8×8 CI matrix HW_(8×8)(2)×CI_(8×8) resulting from amultiplication of the 8×8 CI matrix CI_(8×8) by the second row vectorHW_(8×8)(2) in the 8×8 Hadamard-Walsh matrix, HW_(8×8). The code vectorsin matrix HW_(8×8)(2)×CI_(8×8) are identical to the code vectors inmatrix HW_(8×8)(1)×CI_(8×8), except the order of the vectors is shiftedby four chip positions.

FIG. 33C shows an 8×8 CI matrix HW_(8×8)(3)×CI_(8×8) resulting from amultiplication of the 8×8 CI matrix CI_(8×8) by the third rowHW_(8×8)(3) of the 8×8 Hadamard-Walsh matrix, HW_(8×8). The CI matrixHW_(8×8)(3)×CI_(8×8) includes two binary-phase 8-chip codes, HW_(8×8)(3)and HW_(8×8)(4), two quaternary-phase code vectors, PC4 _(8×8)(2) andPC4 _(8×8)(4), and two complementary octonary-phase code pairs,CI_(8×8)(5) and CI_(8×8)(5)*, and CI_(8×8)(6) and CI_(8×8)(6)*.

FIG. 33D shows an 8×8 CI matrix HW_(8×8)(4)×CI_(8×8) resulting from amultiplication of the 8×8 CI matrix CI_(8×8) by the fourth rowHW_(8×8)(4) of the 8×8 Hadamard-Walsh matrix, HW_(8×8). The code vectorsin matrix HW_(8×8)(4)×CI_(8×8) are identical to the code vectors inmatrix HW_(8×8)(3)×CI_(8×8), except the order of the vectors is shiftedby four chip positions.

FIG. 33E shows an 8×8 CI matrix HW_(8×8)(5)×CI_(8×8) resulting from amultiplication of the 8×8 CI matrix CI_(8×8) by the fifth row vectorHW_(8×8)(5) of the 8×8 Hadamard-Walsh matrix, HW_(8×8). The CI matrixHW_(8×8)(5)×CI_(8×8) includes two binary-phase 8-chip codes, HW_(8×8)(5)and HW_(8×8)(6), two quaternary-phase code vectors, PC4 _(8×8)(5) andPC4 _(8×8)(7), and two complementary octonary-phase code pairs,CI_(8×8)(3) and CI_(8×8)(3)*, and CI_(8×8)(4) and CI_(8×8)(4)*.

FIG. 33F shows an 8×8 CI matrix HW_(8×8)(6)×CI_(8×8) resulting from amultiplication of the 8×8 CI matrix CI_(8×8) by the sixth rowHW_(8×8)(6) in the 8×8 Hadamard-Walsh matrix, HW_(8×8). The code vectorsin matrix HW_(8×8)(6)×CI_(8×8) are identical to the code vectors inmatrix HW_(8×8)(5)×CI_(8×8), except for a cyclic shift of four chippositions.

FIG. 33G shows an 8×8 CI matrix HW_(8×8)(7)×CI_(8×8) resulting from amultiplication of the 8×8 CI matrix CI_(8×8) by the seventh row vectorHW_(8×8)(7) of the 8×8 Hadamard-Walsh matrix, HW_(8×8). The CI matrixHW_(8×8)(7)×CI_(8×8) includes two binary-phase 8-chip codes, HW_(8×8)(7)and HW_(8×8)(8), two quaternary-phase code vectors, PC4 _(8×8)(6) andPC4 _(8×8)(8), and two complementary octonary-phase code pairs,CI_(8×8)(7) and CI_(8×8)(7)*, and CI_(8×8)(8) and CI_(8×8)(8)*.

FIG. 33H shows an 8×8 CI matrix HW_(8×8)(8)×CI_(8×8) resulting from amultiplication of the 8×8 CI matrix CI_(8×8) by the eighth rowHW_(8×8)(8) in the 8×8 Hadamard-Walsh matrix, HW_(8×8). The code vectorsin matrix HW_(8×8)(8)×CI_(8×8) are identical to the code vectors inmatrix HW_(8×8)(7)×CI_(8×8), except for a cyclic shift of four chippositions.

FIG. 34A shows a set 16 octonary codes C(n) that result from themultiplication of the 8×8 CI matrix CI_(8×8) by the rows HW_(8×8)(n) ofthe 8×8 Hadamard-Walsh matrix HW_(8×8). The codes C(n) include at leastsome of the same code vectors CI_(8×8)(n) shown in FIG. 33A through FIG.33H.

FIG. 34B shows auto correlations and cross correlations of the 16octonary codes C(n) shown in FIG. 34A. The correlation relationships arepreferably used to choose orthogonal or quasi-orthogonal code sets fromthe codes C(n). For example, the codes C(1), C(1)*, C(2), C(2)*, C(4),C(4)*, C(7), and C(7)* form an orthogonal eight-code set. Note that thecode pair [C(1), C(1)*] has zero cross correlation with C(2), C(2)*,C(4), C(4)*, C(7), and C(7)* and thus, can be used with these codes toprovide orthogonal code sets. Note that code C(1) has a non-zero crosscorrelation with codes C(1)*, C(5), and C(6). Thus, an orthogonal setmay include codes C(1) and C(5), for example, and exclude codes C(1)*and C(6)*.

The codes C(3), C(3)*, C(5), C(5)*, C(6), C(6)*, C(7), and C(7)* formanother orthogonal eight-code set. Codes C(7), C(3), C(8), C(4), C(1),C(5), C(2), and C(6) form yet another orthogonal eight-code set. Manyother code sets are possible.

FIG. 35 illustrates generalized method and apparatus embodiments of theinvention in which data transmitted on two codes, such as codes C(5)*and C(6), is processed with a single despreading code, such as codeC(1)*. The cross correlations C(5)*C(1)* and C(6)C(1)* are orthogonal toeach other in the complex plane. Thus, throughput of a channel may beincreased by increasing the number of codes on the transmit side withouthaving to increase the number of reference codes on the receive side.

A plurality of data streams s₁(t) and s₂(t) are processed by an encoder3502 to provide at least two coded data streams to an apparatus 3504that combines (e.g., sums) the coded data streams and conveys theresulting signal to a transmitter 3506. The transmitter 3506 may performsignal processing to facilitate coupling the coded data streams into acommunication channel. For example, the transmitter 3506 may perform D/Aconversion, up conversion, mixing, filtering, amplification, beamforming, etc.

A receiver 3508 couples transmitted signals from the communicationchannel. The receiver 3508 may process received signals prior tocoupling the signals to a decoder 3510. For example, the receiver 3508may perform down conversion, mixing, filtering, amplification, A/Dconversion, beam forming, multi-user detection, sub-space processing,etc. The decoder 3510 is adapted to perform CI decoding. For example, atleast one code (such as code C(1)*) is provided to the decoder 3510. Thedecoder 3510 may perform correlation, shifting, or other matched-filteroperations to produce a plurality of decoded signals. If the decodeddata signals overlap each other in time (e.g., they exhibitorthogonality or quasi-orthogonality in the complex plane), the decodeddata signals are passed to a complex-plane processor 3512 that performsan orthogonalizing process (e.g. multi-user detection) to separate theoverlapping data symbols.

A quasi-orthogonal transmission mode provides for transmitting data onat least two codes. Quasi-orthogonal coding may include a plurality ofcodes (such as codes C(5)*, C(6), and C(1)) having non-zero crosscorrelations with at least one despreading code, such as code C(1)*. Thecross correlation C(1)C(1)* maps into cross-correlation spacesC(5)*C(1)* and C(6)C(1)*, thus providing interference. The interferencecan be removed using any well-known technique, including decisionprocessing, interference cancellation, multi-user detection, optimalcombining, etc.

Orthogonal and quasi-orthogonal code sets may be implemented separatelyor simultaneously. Code sets may include combinations of different M-arypolyphase codes. An M-ary code set may include codes with a code length(i.e., number of code chips) that is less than or greater than M. Codesets may include numbers of codes that are less than or greater than thecode lengths. Code sets may include same-length and/or different-lengthcodes.

Although basic CI codes and one family of advanced CI codes aredescribed herein, many other implementations of coding based on CI areclearly anticipated. CI code sets may be selected or manipulated toprovide cross-correlation values that are shifted by π/2.Cross-correlation values may include CI chip values that may beprocessed accordingly. CI codes may be used to generate bi-orthogonaland/or trans-orthogonal CI code sets. CI codes can be generated fromlinear combinations of other CI codes. CI code generation can includeHadamard-Walsh matrix expansion, code concatenation, code interleaving,code superposition, and/or weighted code superposition wherein weightsare applied to one or more code chips.

CI codes may be generated by multiplying CI codes with other codevectors, such as Hadamard Walsh codes, long codes, Golay codes, Barkercodes, Gold codes, Kasami codes, CI codes, etc. A CI code may include atleast one set of CI matrix elements, such as a row, a column, adiagonal, and/or matrix elements selected with respect to somepredetermined pattern or algorithm.

CI code chips may be cyclically shifted, swapped, or otherwisere-ordered. CI codes may be implemented as multi-level codes with one ormore codes that are not necessarily CI codes. Multiple codes includingat least one CI code may be interleaved. CI codes may be interleavedwith same length or different length codes.

CI codes may be implemented in block coding, convolutional coding, turbocoding, Trellis coding, any other form of channel coding, encryption,multiple-access coding, spread-spectrum coding, peak-power mitigation,etc. CI codes may be implemented with orthogonal coding,quasi-orthogonal coding, bi-orthogonal coding, trans-orthogonal coding,or any combination thereof.

CI codes may be generated by convolving at least one set of CI codeswith at least one other set of codes, including one or more of thefollowing: a CI code, a binary direct-sequence code, a channel code, aspreading code, a multiple-access code, etc. CI codes may be providedwith one or more parity-check symbols formed by linear combinations ofdata symbols and/or code chips.

Comparison of CI to Direct Sequence Spread Spectrum

FIG. 36A shows a frequency-domain plot of a data symbol 3601 that isconverted to a wideband spread-spectrum signal 3602 via direct-sequenceprocessing. FIG. 36B shows a frequency-domain plot of the data symbol3601 that is converted to a CI signal having a plurality N of narrowbandcomponents 3603.1 to 3603.N. Although the narrowband CI components arespread across a wide frequency band, the sum of the component bandwidthsis approximately equal to the data-symbol 3601 bandwidth. Thetime-domain characteristics of a superposition of the data symbols3603.1 to 3603.N can be made substantially identical to the time-domaincharacteristics of the data symbol 3601 via an appropriate selection offrequencies and complex amplitudes of the data symbols 3603.1 to 3603.N.Multiple frequency/complex-amplitude combinations may be provided thatsubstantially reproduce the data symbol's 3601 time-domaincharacteristics.

FIG. 37 shows a time-domain plot of a plurality N of narrowband CIcomponents 3702.1 to 3702.N and a data symbol 3701 indicative of asuperposition of the CI components 3702.1 to 3702.N. The apparentduration of the data symbol 3701 is relatively small compared to theduration of each CI component 3702.1 to 3702.N.

The definition of spread spectrum (B. Sklar, Digital Communications,Fundamentals and Applications, Prentice-Hall, Inc., New Jersey, 1988)includes all of the following requirements:

The transmitted signal bandwidth is greater than the bandwidth necessaryto transmit the data.

Spreading is accomplished by a spreading signal.

A receiver uses a replica of the spreading signal to despread a receivedsignal.

The basic implementation of CI is not classified as spread spectrumbecause it does not satisfy all of the requirements of the definition.

The version of CI processing illustrated by FIG. 36B increases thefrequency band over which signal components are distributed, but doesnot increase the total bandwidth of the transmitted signal. The versionof CI processing illustrated by FIGS. 36B and 37 employs more than one“spreading” signal. The data symbols 3601 and 3701 are redundantlymodulated onto multiple carriers and thus, are not spread in theconventional sense. A CI receiver may process received CI signals inmany different ways. One of these techniques involves correlating thereceived signal with a despreading signal. The despreading signal may bea complex conjugate of the spreading signal, rather than a replica.Other techniques include, but are not limited to, providingcomplementary phase shifts to a received CI signal, sampling thereceived CI signal and summing the samples, summing weighted samples ofa received CI signal, and performing an orthogonal transform (such as anorthogonal-frequency Fourier transform).

In at least a few cases, CI/DS-CDMA can be regarded as spread spectrum.A time-domain analysis of a CI/DS-CDMA signal reveals adirect-sequence-like signal even though CI/DS-CDMA is a multicarriersignal. This gives the appearance of a CI signal having been spread witha direct-sequence code. In some implementations of CI/DS-CDMA, CI pulsesmay actually be spread with a direct-sequence code. Even thoughtime-domain characteristics of a CI signal may be made to appear as adirect-sequence signal, many reception techniques other than generatinga code replica may be used to process a received CI/DS-CDMA signal. Forexample, each CI carrier may be processed with a complex-conjugate codein the frequency domain.

Polyphase CI codes comply with the first two definitions of aspread-spectrum signal. However, a complex-conjugate code, rather than acode replica, is usually required to decode received signals.

Direct sequence describes a spectrum-spreading technique that modulatesa data symbol with a pseudo-random noise sequence. A pseudo-random noisesequence is defined by the following attributes:

There is an approximate balance between the number of zeros and thenumber of ones.

Various run-length constraints need to be satisfied with respect tosequences of ones and zeros.

The correlation of a code with its cyclic shift has approximately thesame number of agreements and disagreements.

In the case of CI signals, each data symbol is mapped into a phasespace, which corresponds to a set of complex weights. In the simplestcase, the complex weights are phase shifts. Basic CI signals make use oforthogonality between different phase spaces in the frequency domainrather than orthogonality between different digital sequences in thetime domain. Thus, CI signals are not related to direct-sequencesignals.

CI/DS-CDMA (or CI/DSSS) signals are CI signals and thus, are notdirect-sequence signals. FIG. 38 illustrates frequency-domaincharacteristics of a typical direct-sequence signal 3801 in comparisonto frequency-domain characteristics of a plurality of differentCI/DS-CDMA signaling types. A CI/DS-CDMA signal may have non-overlappingspectral components 3802 or overlapping spectral components 3803.Spectral components 3804 of a CI/DS-CDMA signal may be uniformly spaced.Alternatively, CI/DS-CDMA spectral components 3805 may be non-uniformlyspaced.

CI/DS-CDMA signals differ from digital sequences in that differentCI/DS-CDMA signals can occupy the same set of discreet frequencycomponents, whereas orthogonal digital sequences are characterized byoccupying a common continuous frequency spectrum. Even thoughtime-domain characteristics of a CI/DS-CDMA signal may be similar to adirect-sequence signal, the spectral characteristics of any of theCI/DS-CDMA embodiments are notably different than a direct-sequencespectrum. This frequency-domain difference indicates an important andfundamental difference between CI/DS-CDMA and DS-CDMA.

Direct-sequence signals are processed in the time domain for bothtransmission and reception. For example, a Rake receiver is typicallyused in a direct-sequence system to achieve path-diversity benefits.CI/DSSS signals are advantageously processed in the frequency domain(although they can be processed in the time domain instead of, or inaddition to, the frequency domain). Preferably, CI/DSSS signals arefrequency-domain processed at the receiver to achievefrequency-diversity benefits.

Polyphase CI codes can be implemented in the same way as direct-sequencecodes. However, polyphase CI codes do not conform to the definition ofspread spectrum. CI codes are not necessarily pseudo-random codes. BasicCI codes exhibit some randomness. For example, the phases of CI codechips tend to be uniformly distributed over 2π radians. However,polyphase CI codes typically do not follow the same balance andrun-length constraints of a binary direct-sequence code. Furthermore,cyclic shifts of a CI codes can rotate the phase of the correlationbetween the CI code and its complex conjugate.

In addition to twice the number of orthogonal users, CI codes may beadapted to bi-orthogonal signaling. A set of CI signals may be furtherpartitioned into in-phase and quadrature-phase signals. Variousquasi-orthogonal multi-level phase-shift and/or amplitude-shift codesmay be used.

Overview of CI Multiple-Access Coding

FIG. 39A illustrates a CI code consisting of an n^(th) vector of CI codechips [c_(n1), c_(n2), . . . , c_(nN)] wherein each code chip is mappedinto an orthogonal diversity parameter value [Λ₁, Λ₂, . . . , Λ_(N)]. CIcodes may be used in place of direct-sequence coding when the CI codechips are mapped into the time domain, as shown in FIG. 39B. CI codescan resemble MC-CDMA codes when the code chips are mapped ontoorthogonal frequencies, as shown in FIG. 39C. The order of the codechips with respect to the frequencies may be changed.

CI code chips may be impressed onto different transmit beam patterns orspatial directions, as shown in FIG. 39D. An n^(th) data stream s_(n)(t)is provided to at least one coder 3902 that encodes each data symbols_(n)(t) with respect to a plurality of code chips c_(n1) to c_(nN).Preferably, the code chips c_(n1) to c_(nN) are derived from CI orCI-based codes. The coded symbols are coupled to a beam-forming system3904 that processes the symbols into signals that are suitable fortransmission via a plurality N of transmitter elements 3906.1 to 3906.N.In this case, the transmitted symbols are associated with transmit beampatterns. Each transmitted symbol may be associated with one or morecomplex spatial gain distributions (indicated by complex vectors α_(n))that are transmitted into a communication channel 99.

Many different design variations may be provided to the transmissionsystem shown in FIG. 39D. For example, more than one data stream may becoded and transmitted. A plurality of coded signals corresponding todifferent data symbols may be provided to the same spatial gaindistribution. One or more coded data symbols may be provided redundantlyto multiple beam patterns. The coder 3902 and/or the beam-forming system3904 may interleave the coded data symbols in one or morediversity-parameter spaces. The coder 3902 may provide channel coding tothe data symbols.

Although the transmit beam patterns may be orthogonal, a multipathenvironment typically converts each transmit direction into multipledirections of arrival at a receiver, resulting in flat fading,frequency-selective fading, or inter-symbol interference. Sub-spaceprocessing may be performed to separate the interfering terms, andthereby orthogonalize the received beam patterns. Similarly, appropriatechannel compensation techniques may be performed at the transmitter tohelp orthogonalize transmissions received by the receiver. The qualityof the sub-space channels may vary greatly. However, since codingspreads each multiple-access channel over multiple sub-space channels,sub-space diversity is achieved.

Received spatial-gain patterns are characterized by a plurality ofcomplex vectors β_(nl). The vectors may indicate complex amplitudes ofmultiple (l) paths, directional gain distributions with respect toangles of arrival, complex-values associated with signals collected ateach receiver element 3908.1 to 3908.N′ over some predetermined timeinterval, etc. Received signals are processed in a beam-forming system3910 that may be adapted to perform sub-space processing, diversitycombining, multi-user detection, etc.

The received signals may be down converted to baseband or IF prior to,during, or following beam forming. Sub-space values are provided to adecoder 3912 that may be adapted to perform decoding prior to or afteroptimal combining, multi-user detection, and/or spatial processing. Thedecoder 3912 may provide additional baseband processing, including, butnot limited to, iterative feedback processing, control-signalgeneration, demodulation, demultiplexing, decision processing,constellation mapping, and/or generating confidence measurements.

CI coding may be provided to a transmitter array 3906.1 to 3906.N, asshown in FIG. 39E, such that each code chip c_(n1) to c_(nN)corresponding to at least one multiple-access channel is applied to anindividual spatially separated transmitter element 3906.1 to 3906.N.Sub-space processing at a remote receiver array 3908.1 to 3908.N′separates each code chip of each coded data symbol into spatialsub-spaces. Because the channel quality can vary greatly betweensubspaces, multiple-access coding is used to spread each user's signalover multiple sub-space channels. Thus, impairment of a small number ofsub-space channels does not substantially impair any user's link.Rather, the sub-space channel quality is averaged and provided uniformlyto each multiple-access channel.

FIG. 39F illustrates how multiple-access CI coding can be applied tonon-orthogonal diversity parameter values, such as linear polarizations.A receiver (not shown) may orthogonalize interfering linearpolarizations to separate CI code chips impressed on each polarization.CI code chips c₁ to c_(N) may be impressed upon other non-orthogonaldiversity-parameter values, provided that some sort of multi-channel(e.g., multi-user) detection or subspace processing is performed at thereceiver.

FIG. 39G illustrates how CI code chips c₁ to c_(N) can be impressed ontoorthogonal circular (or elliptical) polarizations. In this case, eachpolarization has an integer number of rotations in a given time intervaland thus, are orthogonal over that time interval. Other orthogonalpolarizations may include opposite-direction rotations and/or π/2 phaseoffsets. Polarization rotations resemble sub-carrier processing.Consequently, circular or elliptical polarizations can be processed inthe same way as CI carriers. Orthogonal polarizations may be redundantlymodulated. CI phase spaces may be extended to polarization and/or otherdiversity parameters. Multiple data symbols may be modulated onto eachpolarization signal and provided with polarization and/or signal phaserelationships to orthogonalize the interfering data symbols.

A two-dimensional circular-polarized signal has linear vertical andhorizontal components that can be described by in-phase andquadrature-phase sinusoidal functions:

A _(vert) =A ₀ sin(2πƒ_(n) t+φ)

A _(horiz) =A ₀ cos(2πƒ_(n) t+φ)

In the case where the rotational frequencies ω_(n)=2πƒ_(n) areorthogonal, the frequencies ƒ_(n) can be expressed by:

ƒ_(n)=ƒ₀ +nƒ _(s),

where ƒ₀ is an offset frequency, n is an integer, and ƒ_(s) is a shiftfrequency. A symbol modulated onto one or more of the frequencies isprovided with a symbol period T_(s) expressed by:

T _(s) =l/ƒ _(s)

where l is some integer.

In order to illustrate reception of orthogonal circular polarizedsignals, the value of l is set to one. A circular-polarized receiverprovides in-phase and quadrature-phase multiplicative terms to thevertical and horizontal components of the received signal. A receivedsymbol r(t) is evaluated by integrating or summing the receiver outputover the symbol period T_(s):

${r(t)} = {\int_{0}^{T_{s}}{\left( {\sum\limits_{n,n^{\prime}}^{\;}\left( {{A_{n}A_{n^{\prime}}^{\prime}\ {\sin \left( {2\pi \; f_{n}t} \right)}{\sin \left( {2\pi \; f_{n^{\prime}}t} \right)}} + {A_{n}A_{n^{\prime}}^{\prime}{\cos \left( {2\pi \; f_{n}t} \right)}{\cos \left( {2\; \pi \; f_{n^{\prime}}t} \right)}}} \right)} \right){\partial t}}}$

where ƒ_(n) is the frequency of the receiver's circular polarization andƒ_(n′) is the circular-polarization frequency of the received signal.Amplitudes A_(n) and A′_(n′) correspond to receiver gain and receivedsignal amplitude, respectively.

The expression for r(t) can be separated into two sets of equationscorresponding to n=n′ and n≠n′:

     r_(nn)(t) = A_(n)A_(n)^(′)∫₀^(T_(s))(cos²(2π f_(n)t) + sin²(2π f_(n)t))∂t${r_{{nn}^{\prime}}(t)} = {\int_{0}^{T_{s}}{\left( {\sum\limits_{n \neq n^{\prime}}^{\;}\left( {A_{n}{A_{n^{\prime}}^{\prime}\left( {{{\sin \left( {2\pi \; f_{n}t} \right)}{\sin \left( {2\pi \; f_{n^{\prime}}t} \right)}} + {{\cos \left( {2\pi \; f_{n}t} \right)}{\cos \left( {2\pi \; f_{n^{\prime}}t} \right)}}} \right)}} \right)} \right){\partial t}}}$

The equation for r_(nn′)(t) simplifies to the value A_(n)A_(n)·T_(s).

Phase modulation or phase misalignment can cause a phase offset φ_(b)between the receiver's polarization angle and the angle of the receivedpolarized signal. Any such phase offset φ_(b) causes a modulation of thereceived symbol r_(nn)(t) by a factor of cos(φ_(b)).

The equation for r_(nn′)(t) can be simplified to the expression:

$\begin{matrix}{{r_{{nn}^{\prime}}(t)} = {\int_{0}^{T_{s}}{\sum\limits_{({n - n^{\prime}})}^{\;}{A_{n}A_{n^{\prime}}^{\prime}\ {\cos \left( {2{\pi \left( {n - n^{\prime}} \right)}f_{s}t} \right)}\delta \; t}}}} \\\left. {= {\frac{1}{2{\pi \left( {n - n^{\prime}} \right)}f_{s}}\left( {\sum\limits_{n - n^{\prime}}^{\;}{A_{n}A_{n^{\prime}}^{\prime}\ {\sin \left( {2{\pi \left( {n - n^{\prime}} \right)}f_{s}t} \right)}}} \right._{0}^{T_{s}}}} \right) \\{= 0}\end{matrix}$

Thus, r_(nn′)(t)=0 for all non-zero integer values of (n−n′). Thisillustrates how the multicarrier orthogonality condition can be appliedto signals having circular polarization. Similarly, orthogonal sets ofelliptically polarized signals may be developed.

CI Multiple-Access Transceiver

FIG. 40A illustrates a CI transceiver of the invention. An informationsignal, such as a stream of data bits or data symbols may be processedwith an optional coder/interleaver 4001. The coder/interleaver 4001 mayperform channel coding, error-correction coding, interleaving,puncturing, and/or any other type of data processing that is typicallyperformed prior to multiple-access or spread-spectrum coding.

Data symbols are coupled to a CI encoder 4002, such as a modulator, thatimpresses the data symbols onto at least one CI code generated by aCI-code generator 4003. A CI-code generator, such as the CI-codegenerator 4003, is any algorithm, device, or system adapted to generateCI codes as described and/or defined herein. A CI encoder, such as theCI encoder 4002, includes any algorithm, device, or system adapted tocombine, merge, or otherwise impress at least one data symbol onto aplurality of CI code chips. The CI encoder 4002 may impress each CI codechip onto one or more diversity-parameter values prior to or afterimpressing data symbols onto the CI code. A CI code may be impressedonto at least one IF carrier. The CI encoder 4002 may performmultiplexing. For example, the CI encoder 4002 may encode data streamsonto different CI codes. The CI encoder 4002 may employ other diversityparameters on which to multiplex multiple data streams.

The encoded data is coupled to a transmit coupler 4004 that optionallyperforms carrier-frequency (e.g., RF or optical) processing on theencoded data prior to coupling the encoded data into a communicationchannel 99. The transmit coupler 4004 may up convert baseband or IF datasymbols to RF or optical signals. The transmit coupler 4004 may modulateone or more carriers with the encoded data symbols prior totransmission. The transmit coupler 4004 may impress CI code chips ontoone or more sets of diversity-parameter values. For example, thetransmit coupler 4004 may include a beam former (not shown).

A receive coupler 4006 couples received signals from the communicationchannel 99 and converts the signals to some form (e.g., baseband) thatfacilitates processing by the rest of the receiver portion of thetransceiver. The receive coupler 4006 typically performscarrier-frequency processing on the received signals. The receivecoupler 4006 may down-convert the received signals to baseband or IFsignals. The receive coupler 4006 may perform diversity combining,multi-user detection, sub-carrier processing, interference cancellation,sub-space processing, beam forming, channel characterization, channelcompensation, and/or various types of adaptive processing.

The receive coupler 4006 provides CI-encoded data symbols to a CIdecoder 4007, such as a demodulator, that also receives an input fromthe CI-code generator 4003. The CI decoder 4007 extracts or estimatesthe data symbols encoded with at least one CI code. Received Datasymbols are typically distorted by the communication channel 99. Thus,the CI decoder 4007 may include an optimal receiver, a channelestimator, and/or a channel compensator.

Decoded data symbols may be optionally processed in a decode-signalprocessor 4008. The decode-signal processor 4008 may be integrated withthe CI decoder 4007. The decode-signal processor 4008 may include adecision processor (not shown) that generates hard and/or softdecisions. The decode-signal processor 4008 may include a feedback loop(not shown) to the CI decoder 4007 and/or the receive coupler 4006 toadjust processing with respect to one or more signal-qualitymeasurements. The decode-signal processor 4008 may convert decoded datasymbols into an information bit stream.

A CI decoder, such as the CI decoder 4007, is any algorithm, device, orsystem adapted to decode at least one CI-encoded signal. A CI-encodedsignal typically is a CI-encoded information-bearing signal. A CIdecoder may convolve and/or correlate at least one decode signal withthe at least one CI-encoded signal to extract the at least oneinformation signal or at least one estimate of the information signal. ACI decoder may perform hard and/or soft estimates of the informationsignal. A CI decoder may include multiple decoders and perform aniterative process of conveying soft decisions between the multipledecoders. A CI decoder may perform one or more of the following:de-interleaving, channel decoding, multiple-access decoding,demultiplexing, demodulating, decrypting, channel analysis, channelcompensation, despreading, error detection, and error correction. A CIdecoder may provide corrective phase offsets to compensate for non-zerophase signals, channel distortion, phase jitter, and/or phase offsetsapplied to transmitted signals to achieve some predetermined objective,such as minimizing PAPR, enhancing security, etc.

A decode-signal processor, such as the decode-signal processor 4008, isany algorithm, device, or system that is adapted to process at least onedecoded signal. The decode-signal processor may provide hard and/or softdecisions when evaluating the decoded signal. A decode signal processormay include one or more quantizers, comparators, iterative decoders,feedback loops, interference cancellers, optimal detectors, and/or anyother devices that contribute to a decision and/or detection process. Adecode-signal processor may provide other types of decoding in additionto CI decoding. For example, a decode-signal processor may decodeblock-encoded signals, convolutional-encoded signals, encrypted signals,turbo-coded signals, compressed signals, etc. The decode-signalprocessor may perform demultiplexing and/or de-interleaving, ifnecessary. The decode-signal processor may perform multi-user detection,optimal combining, diversity reception, and/or any other techniquedesigned to enhance signal quality by mitigating the effects ofinterference, distortion, and/or noise.

FIG. 40B illustrates one embodiment of the CI-code generator 4003. ACI-symbol generator 4109 generates a plurality of CI symbols that arecoupled to a symbol combiner 4110. The symbol combiner 4110 groups theCI symbols to generate one or more CI codes.

A CI-symbol generator, such as the CI-symbol generator 4109, includesany algorithm, system, or device adapted to generate a plurality of CIsymbols. CI symbols include CI base symbols, which are symbols generatedfrom any integer-number of rotations of a vector through the complexplain. CI symbols may include at least one set of polyphase symbols. CIsymbols may be discreet-valued or continuous-valued numbers orfunctions. CI symbols may be values derived from at least one invertibletransform function, such as a Fourier transform, a Laplace transform, aWalsh transform, a wavelet transform, etc. CI symbols may include linearcombinations of other CI symbols, linear combinations of CI symbols withother code symbols, CI symbols modulated with code sequences from apredetermined code set including one or more of the following:spread-spectrum codes, multiple-access codes, channel codes, encryptioncodes, multi-level codes, compression codes, hybrid codes, and CI codes.

A symbol combiner, such as the symbol combiner 4110, includes anyalgorithm, system, or device adapted to group CI symbols to generate atleast one CI-chip sequence. A symbol combiner may append, concatenate,interleave, shift, puncture, or re-order one or more CI symbols sets. Asymbol combiner may combine CI symbols with other types of symbols. Asymbol combiner may provide a CI chips sequence with at least oneparity-check symbol.

FIG. 41A illustrates general steps of a transmitting method of thepresent invention. An information signal s(t) is optionally encodedand/or interleaved 4101. Encoding may include code puncturing.Preferably, coding includes CI or CI-based coding. Thecoding/interleaving step 4101 may include generating or otherwiseacquiring symbol values to be impressed onto multiple carriers. Theinformation signal may be provided with predetermined training symbolsin a training symbol injection step 4102. Training symbols may be usedfor channel estimation, signal-quality estimations, synchronization,etc. An IFFT 4103 or equivalent process impresses the coded data symbolsonto a plurality of carriers. Optionally, a cyclic prefix may be addedto the coded data symbols. An FIR filtering and interpolation step 4104is performed prior to preparing the resulting signal for transmissioninto a communication channel (not shown).

Various steps and systems adapted to perform the steps shown in FIG. 41Amay be included in transmission systems and methods pertaining to otheraspects and embodiments of the invention. Furthermore, varioussignal-processing steps that are typically performed in transmissionsystems may be included herein. For example, pre-equalization stepsand/or systems may be included in the transmitter embodiments shown inFIG. 41A. An array processing step (not shown) may be performed, such asafter FIR filtering and interpolation 4104. Alternatively, arrayprocessing may be integrated into the coding 4101, IFFT 4103, and/or FIRfiltering 4104 steps.

FIG. 41B illustrates general steps of a reception process of the presentinvention. One or more transmitted signals are coupled out of acommunication channel (not shown) and provided to an FIR filtering anddecimation step 4105. Filtered signals may be processed in asynchronization step 4111 to control the timing of various receptionprocesses, such as, but not limited to a cyclic prefix removal and FFTstep 4106. Complex-amplitude values associated with individual carrierfrequencies, such as estimates obtained via known training symbolsand/or unknown data symbols, may be used in a channel-estimation step4113. The channel estimation step 4133 can facilitate the generation ofweights (e.g., array-processing and/or CI combining weights).

Array processing 4107 is performed to achieve some preferred combinationof system capacity (i.e., sub-channel generation) and signal quality(i.e., diversity combining). For example, array processing may includespatial interferometry multiplexing and/or any other form of arrayprocessing. Array processing 4107 may be assisted by aninterference-estimation step 4116. A CI combining step 4118 may beperformed in conjunction with the array-processing step 4107 and/or adecoding and de-interleaving step 4108. Alternatively, either or boththe array-processing step 4107 and the decoding and de-interleaving step4108 may perform CI combining 4118. The decoding and de-interleavingstep 4108 performs any necessary deinterleaving of data symbols receivedfrom the array-processing step 4107 prior to, or following decoding.Decoding may include channel, multiple access, spread spectrum,encryption, and/or other decoding processes.

10. CI Channel Coding

FIG. 42 shows a system diagram of a CI transceiver. An informationsource 4201 provides data symbols to a CI coder/interleaver 4211. Amodulator 4221 is adapted to modulate the coded symbols onto one or morecarriers that are transmitted by a transmitter 4222 into a communicationchannel 99. The channel 99 may be characterized by AWGN and/ormultipath. Similarly, other types of channel distortion may beconsidered. A receiver 4224 couples the transmitted signals from thechannel 99. A demodulator 4225 retrieves symbols from the receivedsignal. A CI decoder/de-interleaver 4235 decodes (and deinterleaves, ifnecessary) the received symbols into information symbols that areoptionally processed in an information processor or sink 4236.

Channel coding provides signal transformations that are designed toimprove communication performance by enabling transmitted signals tobetter withstand the effects of various channel impairments (e.g.,noise, fading, interference). CI channel coding may include waveformcoding and/or structured sequences. CI waveform coding (such as CI,Trellis code modulation, convolutional CI coding, CI turbo coding, M-arysignaling, orthogonal coding, bi-orthogonal coding, trans-orthogonalcoding, etc.) transforms waveforms to make them less subject to error.CI-structured sequences transform a data sequence into one or moresequences having structured redundancy. Redundant data symbols or bitsare used for detecting and/or correcting errors.

CI coding may include replacing a data set with an orthogonal codewordset. In one embodiment, the decoder may multiplex multiple coded datasymbols together by providing an orthogonal codeword set. An orthogonalCI codeword set may be selected such that each codeword vector has zeroprojection onto all other CI codeword vectors except for its complexconjugate. The receiver's decoder 4235 may include multiple matchedfilters (or equivalent systems or algorithms) that output zero unless acorresponding encoded data symbol is received.

The bandwidth requirements for bi-orthogonal CI codes are half of therequirements for comparable orthogonal codes. Bi-orthogonal codes haveslightly better performance over orthogonal codes because antipodalsignal vectors have better distance properties than orthogonal signals.Trans-orthogonal (e.g., simplex) codes, when compared to orthogonal andbi-orthogonal codes, require the minimum SNR for a particular symbolerror rate. Channel codes may be overlaid onto multiple-access codes.Depending on the processing gain of the multiple-access codes, channelcoding may not require additional bandwidth.

In one embodiment, the coder 4211 maps data symbols to CI code wordsusing a look-up table. In another embodiment, the CI code words aregenerated with respect to each data symbol. Code-word generation may beperformed with a CI code generation matrix G. All CI codes of a givenset of CI code words can be constructed from a combination of linearlyindependent code vectors that form the CI code generation matrix G.

Although code generation is described with respect to basic CI codes,orthonormal basis vectors and a corresponding CI code generation matrixmay be constructed for advanced CI codes. Each code in a basic CI codeset can be defined by a different number of full rotations in thecomplex plain. For example, an orthonormal basis for a set of 64 basicCI codes can be defined by the CI code generation matrix:

$G = \begin{bmatrix}{C\left( {{rotations} = 1} \right)} \\{C\left( {{rotations} = 2} \right)} \\{C\left( {{rotations} = 4} \right)} \\{C\left( {{rotations} = 8} \right)} \\{C\left( {{rotations} = 16} \right)} \\{C\left( {{rotations} = 32} \right)}\end{bmatrix}$

where C(rotations=m) is a code vector corresponding to:

C(m)=e ^(imφ′)(1,e ^(imφ) ,e ^(i2mφ) , . . . , e ^(i(N−1)mφ))

Since this basic CI code set is totally defined by G, the coder 4211needs to store only k rows of G instead of the 2^(k) vectors of the CIcode. Furthermore, since the first half of the each row vector C(m) of Gis the same as the second half (except C(1)'s first and second halvesdiffer by a factor of −1), the coder 4211 and decoder 4235 need onlystore one half of each row vector C(m).

A CI receiver may perform error detection using any of severaltechniques. Symmetry relationships between the first and second halvesof a received code can be exploited to determine whether an erroroccurred. Other relationships between code symbols may be used toprovide error detection and/or correction. For example, adjacent CI codesymbols (except for the all-ones code) are typically not identical.Depending on the code, the values of adjacent code symbols change in apredetermined way. For example, adjacent code chips of the basic codeC(m) differ by e^(imφ). A parity-check matrix H (defined by theequation, GH^(T)=0) can be used to test whether a received vector is amember of a codeword set. The decoder 4235, upon detecting an error, mayperform forward error correction and/or request a retransmission.Preferably, the decoder 4235 estimates the transmitted code vector usingsome sort of optimizing strategy, such as the maximum-likelihoodalgorithm. The receiver may erase ambiguous signals. The decoder 4235may implement error correction that corrects erasures or correctserasures and errors simultaneously.

It is preferable that the coder 4211 select codes that maximize theHamming distance between codes. An advantage of using CI polyphase codesis that they provide a superior Hamming distance compared to binarycodes. For example, an (n,k)=(8,3) binary code has an n-tuple space of2n=28=256 binary words, of which 2^(k)=2³=8 are code words. Anoctonary-phase (m=8) (8,3) code has an n-tuple space of 2^(mn)=2⁶⁴octonary words. The fraction of words that are code words decreasesdramatically with increasing values of m. When a small fraction of then-tuple space is used for code words, a large Hamming distance can becreated.

CI codes may be processed as cyclic codes, which are described in manyprior-art references, such as B. Sklar, Digital CommunicationsFundamentals and Applications, Prentice-Hall, Inc., New Jersey, 1988.For example, components of a CI code vector C=(C₀, C₁, . . . , C_(N−1))can be treated as coefficients of a polynomial U(X), as follows:

U(X)=u ₀ +u ₁ X+u ₂X² + . . . +u _(N−1) X ^(N−1)

where X=e^(i2πnk/N), and where k is the order of the code: k=0, 1, . . ., N−1. Well-known cyclic code processing may then be performed.

FIG. 43A shows a (2,1) polyphase (M-ary) convolutional coder withconstraint length K=3. There are n=2 modulo-M adders. The code rate k/nis ½. The coder 4211, when implemented with a convolutional coder, mayinclude phase shifters or a tapped delay line to effect phase shifts.The function of the polyphase convolutional encoder can be expressedwith an M-ary trellis diagram shown in FIG. 43B. A decoding processinvolves choosing a path through the trellis with respect to optimizingsome performance metric, such as a likelihood or log-likelihood metric.There are many possible paths that are not shown in FIG. 43B. Thedecoder 4235, when implemented as a convolutional decoder, may includephase shifters or a tapped delay line to effect phase shifts. Thedecoder 4235 may convert received signals to polyphase or modulo-Msymbols prior to decoding in a microprocessor (not shown).

The decoder 4235 may be configured to discard paths that are not goodcandidates for the maximum likelihood sequence. Thus, the decoded pathis chosen from a reduced set of possible paths. This reduces thedecoding complexity. Any of several algorithms may be used to provideapproximate solutions to the maximum likelihood decoding problem,including sequential and threshold algorithms. A convolutional decodermay include a Viterbi, sequential, and/or a feedback decoder.

The coder 4221 may include an interleaver and the decoder 4235 mayinclude a de-interleaver. Interleaving a coded message beforetransmission and de-interleaving after reception causes bursts ofchannel errors to be spread out in one or more sets ofdiversity-parameter values. This allows the decoder 4235 to handlebursts of errors as random errors.

Interleavers typically make use of time diversity. However, otherdiversity parameters may be exploited instead of, or in addition totime. For example, interleaving may be performed across one or morediversity-parameter values of each transceiver, such as frequency,polarization, phase space, beam direction, code, mode, etc. Interleavingmay be exploited across multiple receivers. For example, subspaces(spatial and/or non-spatial) may be exploited for interleaving.

The demodulator 4225 may make a hard decision as to the value of areceived symbol and pass that value to the decoder 4235. The demodulator4225 may provide the decoder 4235 with an unquantized or over-quantized(quantization level>M) value to the decoder 4235. Sending anover-quantized value to the decoder 4235 is equivalent to sending ameasure of confidence along with a code-symbol value. The decoder 4235may include multiple decoders (not shown) that provide soft-decisionvariables to each other in an iterative fashion to optimize decodingperformance.

FIG. 43C illustrates polyphase channel coding that may be provided by aCI channel coder coupled to a modulator adapted to perform high-level(e.g. M-ary) modulation. The codes illustrated in FIG. 43C provide forchannel coding without increasing the bandwidth of the transmissionsignal. In this case, a plurality of code values of a code vector 4303(which represents a CI-encoded superposition of data symbols d₁ to d_(N)4301) may be expressed as symbols w_(n) characterized by a higher-orderconstellation of symbol values w_(n) (n=1, . . . , N) compared to thedata symbol values d₁ to d_(N).

The code vector 4303 may be generated from a product of a data-symbolvector 4301 with a CI code matrix. In this example, contributions ofdata symbol −1 to the code vector 4303 are determined by CI code valuesin a corresponding column 4312 of a CI code matrix. The code valuew_(n)=−2i is an expression (e.g., a sum) of a linear combination ofweighted data symbols expressed by a scalar product of the data-symbolvector 4301 with a row 4311 of the CI code matrix. Although binary datasymbols 4301 are shown, the data symbols d₁ to d_(N) may be expressed byhigher-order modulations.

In the case of basic CI coding (i.e., CI code values c_(nn′)=1 for n=1or n′=1), symbol w₁ may be used as a simple parity check of the datasymbol values d₁ to d_(N). Other parity checks may be represented by theother symbol values w_(n). The parity checks may be used in errordetection and/or symbol estimation. Parity checks may be part of aniterative optimization process that employs a multi-step methodology(e.g., turbo decoding) to reduce the effects of noise and/orinterference. Data-symbol redundancy may be provided in CI channelcoding via any additional form of channel coding (e.g., Trellis coding,convolutional coding, block coding, etc.). Quasi-orthogonal spaces(i.e., orthogonal positions or codes provided by pulse overlapping in CIpulse-shaping) may be used to convey coded and/or otherwise redundantdata symbols.

In one set of embodiments, the symbol values w_(n) may be characterizedby a set of phases. In another set of embodiments, the symbol valuesw_(n) may be characterized by a set of multi-level amplitudes andphases. In some embodiments, the symbol values w_(n) may becharacterized, at least in part, by modulo-N combining of a plurality ofcoded data symbols. Symbols w_(n) may be provided by any combination ofgenerating (e.g., combining sets of coded symbols) and acquiring (e.g.,selecting values from a look-up table) symbol values.

CI channel decoding may employ Trellis decoding, such as illustrated byFIG. 43D. Any of various Trellis decoding algorithms, such as theViterbi algorithm, may be employed. Alternatively, one or more types ofcorrelation or matched-filtering algorithms may be performed to providedata-symbol estimates. In some applications, the symbols w_(n) may becombined to provide estimates of the data symbols. For example, eachdata-symbol estimate may be generated by providing at least one set ofphase shifts (i.e., a phase-space vector) to the symbols w_(n) andcombining the phase-shifted symbols w_(n). Noise estimates may begenerated using any combination of expected data-symbol values d₁ tod_(N), code values w_(n), and parity-check values (e.g., w_(n)). Noiseestimates may be generated with respect to measurement parametersassociated with redundant sets of CI-encoded data symbols. Noiseestimates and/or data-symbol estimates may be generated iteratively. Forexample, noise and/or data-symbol estimates may be adjusted or selectedand evaluated with respect to probability of error using any combinationof signal-quality measurements.

FIG. 44A shows a possible embodiment of the coder 4211. A block coder4401 encodes input data symbols with at least one block code. The blockencoded symbols are then encoded in a convolutional coder 4402 togenerate convolutional-encoded, block-encoded data symbols.

FIG. 44B shows a convolutional coder 4402 and a block coder 4401switched in order with respect to the coder shown in FIG. 44A. Theoutput signal is a block-encoded, convolutional-encoded data sequence.One or more interleavers (not shown) may be provided in FIGS. 44A and/or44B. The interleavers may be provided before or after either or both theblock coder 4401 and the convolutional coder 4402.

FIG. 45A and FIG. 45B illustrate possible embodiments for the decoderscorresponding to the coders shown in FIG. 44A and FIG. 44B,respectively. Similarly, one or more de-interleavers (not shown) may beprovided to the decoders with respect to any interleaver provided to thecoders.

FIG. 46 illustrates basic components of a turbo coder/decoder systemthat may be used to process CI codes. A data sequence is encoded with atleast two error-correction codes applied by at least two coders 4601 and4602. The data sequence is interleaved by an interleaver 4604 prior toencoding by the second coder 4602. The coded data symbols aremultiplexed together into a single symbol stream that may be processedby a transmit processor 4608 before being coupled into a communicationchannel 99.

Received signals from the communication channel 99 are optionallyprocessed by a receiver processor 4610. Basic received signal processingtasks, such as amplification and filtering, may be performed by thereceiver processor. A baseband processor 4612 may include a matchedfilter and sampler or some other systems or software adapted to convertthe received signals into a symbol stream. A demultiplexer 4614demultiplexes the resulting symbol stream into two symbol streams. Eachsymbol stream is processed in one of a plurality of decoders, such asdecoders 4621 and 4622.

Turbo coding combats random and burst errors by combiningerror-correction coding and interleaving. A first code encodes a datastream. A second code encodes an interleaved version of the data stream.Each decoder 4621 and 4622 provides de-interleaving (if necessary) anddecoding. The output of one decoder 4621 aids the other decoder 4622 inan iterative fashion. Soft outputs from each decoder 4621 and 4622 areprovided to the other decoder 4622 and 4621. Soft outputs indicatereliability of a symbol estimate produced by a decoder. A soft-decisionvalue produced for each bit in a symbol includes an estimate of thesymbol and the relative probability of a particular bit having aparticular value. Preferably, the first soft decision is produced by thedecoder 4621 or 4622 provided with the highest signal strength. Theresulting soft-decision variable typically has higher reliability and,thus, reduces the number of iterations.

The codes applied by the coders 4601 and 4602 may be CI codes. Themultiplexer 4606 and demultiplexer(s) 4614 may perform CI processingand/or sub-space processing. Different coded symbols may be multiplexedonto different CI carriers, different CI phase spaces, differentsubspaces, etc. The coded symbols may be coded with respect to somemultiple-access code as part of the multiplexing procedure. Preferably,the multiple-access code spreads the symbols to provide the decoderswith diversity benefits. Multiple-access-encoded symbols may be spreadacross different diversity-parameter values. For example, CI and/orbinary-phase codes can spread a signal across a broad frequency band,multiple time intervals, multiple subspaces, etc. This spreading canprovide the coded symbols with diversity benefits, thus reducing thenumber of decoding iterations.

The demultiplexers 4614 may include an optimal combiner (not shown). Thedemultiplexer 4614 may include other types of receivers and receivercomponents including, but not limited to, a multi-user detector, aninterference canceller, a spatial interferometry demultiplexer, and/orany diversity-parameter beam former, including a spatial beam former.The demultiplexers 4614 may be provided with soft-decision values fromeither or both of the decoders to facilitate optimal reception.Variations to the function of the demultiplexers 4614 may be providedwith respect to SNR, BER, and/or probability of error, as determined bythe soft-decision values.

CI codes may be implemented in various types of channel coding. In oneset of embodiments of the invention, one or more data symbols s_(n)(t)are mapped into a plurality of CI symbols represented by CI carrierweights w_(n)(t).

FIG. 47A illustrates a set of data symbols 4701 that are impressed ontoa plurality of CI pulses 4702. FIG. 47B illustrates a modulated pulsestream 4703 resulting from impressing the data symbols 4701 onto thepulse stream 4702. FIG. 47C illustrates a plurality of CI symbolsrepresented by a plurality of CI carrier weights w_(n)(t). Asuperposition of the carriers 4705 produces the modulated pulse stream4703.

The data symbols 4701 may be binary symbols (as shown) or symbolsderived from a more complex alphabet. The CI pulse stream 4702 mayinclude overlapping and/or non-overlapping pulses. The pulses of thepulse stream 4702 may be uniformly and/or non-uniformly positioned intime. Data symbols 4701 may be impressed onto the pulses via any type ofmodulation, including amplitude modulation, frequency modulation, phasemodulation, time-offset modulation (e.g., pulse-position modulation),polarization modulation, or any combination thereof.

The CI carriers 4705 may be characterized by overlapping and/ornon-overlapping carriers. The carriers 4705 may be uniformly and/ornon-uniformly spaced-in-frequency carriers. The weights w_(n)(t)corresponding to the carriers 4705 depend on the carrier frequencies.The weight values w_(n)(t) also depend on any carrier frequencyamplitude profiles, such as may be provided to shape the time-domainpulses and/or provide for frequency-domain shaping. Similarly, weightvalues w_(n)(t) depend on any phase coding provided to the carriers,such as to reduce the PAPR of the pulses.

In one set of embodiments of the invention, data symbols s_(n)(t) areliterally impressed onto CI pulses. The CI carriers are processed toprovide carrier weights w_(n)(t). In another set of embodiments, datasymbols s_(n)(t) are impressed onto non-CI signals that are decomposedinto CI carrier components to provide carrier weights w_(n)(t). In yetanother set of embodiments of the invention, the descriptions of CIcarrier processing are merely a representation of a mathematical processthat derives CI symbols w_(n)(t) corresponding to a given set of datasymbols.

The CI symbols can optionally be interleaved prior to being impressedonto a plurality of diversity-parameter values. In one embodiment of theinvention, the CI symbols are transmitted as a serial symbol stream. Inanother set of embodiments, CI symbols are transmitted in parallel. Forexample, CI symbols may be transmitted on multiple frequencies, multiplesubspaces, etc. Various combinations of diversity parameters and serialand/or parallel processing may be implemented.

Each CI symbol w_(n)(t) corresponding to a particular data set s_(n)(t){n=1 . . . , N} may convey the same plurality of data symbols s_(n)(t).Interferometry between the CI symbols w_(n)(t) enables the data symbolss_(n)(t) to be extracted. If some of the CI symbols w_(n)(t) arecorrupted or lost, the encoded data symbols s_(n)(t) can still berecovered with minimal degradation. This type of CI coding enables errorcorrection without increasing bandwidth requirements or reducingthroughput. Furthermore, CI coding combined with quasi-orthogonal pulseshaping enables simultaneous benefits of error-correction enhancementand increased throughput.

FIG. 48 shows one of many possible embodiments of a CI-code transmitterand a CI-code receiver. A set of data symbols 4701 is processed by a CIsymbol generator 4820. The CI symbol generator 4820 may incorporate anysystem design that processes received data symbols to generate at leastone set of CI symbols. In this case, a pulse waveform generator 4801processes input data symbols s_(n)(t) to produce a plurality ofmodulated CI waveforms 4703 that are processed with a Fourier transform4802 into a plurality of CI symbols w_(n)(t). An optionalparallel-to-serial converter 4803 provides a serial symbol stream outputfrom the CI symbol generator 4820.

Optionally, the CI symbols w_(n)(t) may be interleaved by an interleaver4804 prior to being provided to a transmission system 4805. Thetransmission system 4805 may perform modulation, multiple-accessprocessing, multiplexing, coding, D/A processing, spreading, frequencyconversion, filtering, amplification, and/or beam forming prior tocoupling transmission signals into a communication channel 4899.

A receiver couples transmitted signals from the communication channel4899 into a receiver system 4806. The receiver system 4806 may performbeam forming, amplification, filtering, down conversion, despreading,decoding, demultiplexing, multiple-access processing, demodulation, A/Dprocessing, data storage, and/or other typical receiver processingtechniques. Received signals may optionally be processed by achannel-compensation system 4807. If necessary, received signals may bedeinterleaved in a deinterleaver 4808 prior to processing by a CI signalprocessor 4830.

The CI signal processor 4830 receives a set of samples that may includedistortion and/or interference resulting from propagation through thechannel 4899. The CI signal processor 4830 processes the samples, whichmay directly or indirectly be in the form of CI symbols. In this case, aserial-to-parallel converter 4809 prepares a serial input forinverse-Fourier processing 4810 followed by waveform processing 4811.The waveform processor 4811 may sample a time-domain waveform resultingfrom a combination (e.g., a superposition) of CI symbols or waveformsrepresented (e.g., weighted) by CI symbols.

FIG. 49 illustrates the relationship between CI symbol values w_(n) anddata symbols s_(n) CI code chip values are arranged in columns withrespect to phase spaces, such as phase space (column) 4901. As shownpreviously, a phase space is analogous to a pulse position. The phasespaces (i.e., pulse positions) may be orthogonal or quasi-orthogonal.Thus, the number of CI symbols w_(n) may differ from the number of datasymbols s_(n). Each data symbol value s_(n) is impressed upon a phasespace such that each set of CI code chip values expresses the value ofthe corresponding data symbol s_(n). Each code-chip value is analogousto a complex weight applied to a particular CI carrier such that asuperposition of the carriers produces a CI waveform bearing the datasymbol value s_(n) at a particular pulse position.

A CI superposition waveform bearing multiple data-symbol/pulse-positioncharacteristics can be created by applying weights to CI carriers thatcorrespond to sums of carrier weights for eachdata-symbol/pulse-position. Similarly, each CI symbol, such as symbolw₂, may be represented as a sum of a row of data-bearing CI code chips,such as row 4902.

Decoding may include any appropriate inverse of the coding operationrepresented by FIG. 49. For example, to extract an n^(th) data symbolvalue s_(n) from a vector of received CI symbol values w, the complexconjugate of a vector of the n^(th) phase space (or CI code) values,w*_(n), may be correlated with the received CI symbol vector w.Alternative equivalent decoding processes may be performed. The decodingprocess may be performed with respect to one or more combiningtechniques, such as, but not limited to, MMSE, EGC, maximum likelihoodcombining, or any combination thereof. Decoding may include turbodecoding, Trellis decoding (e.g., Viterbi decoding), block decoding,etc.

FIG. 50 illustrates basic components of a CI coding system and a CIdecoding system. A data symbol stream 4701 is processed by a CI symbolgenerator 5020 that outputs a plurality of CI symbol values w_(n)representing a coded version of the data symbols s_(n). The symbolsw_(n) may optionally be interleaved by an interleaver 5004 prior tobeing prepared for transmission into a communication channel 5099 by atransmission system 5005. The symbols w_(n) are typically multiplexedonto one or more diversity-parameter spaces prior to being transmitted.

A receiver system 5006 couples transmitted signals from the channel5099, performs any necessary processing, such as filtering,amplification, demultiplexing, de-spreading, decoding, and/or beamforming, prior to outputting an IF or baseband digital signal.Optionally, channel compensation 5007 may be performed to mitigateeffects of channel distortion and/or interference. Any necessaryde-interleaving processes 5008 may be performed prior to processing by aCI signal processor 5030.

The CI signal processor 5030 processes received CI symbols w′_(n) toproduce data-symbol estimates 4701′. The data-symbol estimates 4701′ maybe output to additional signal-processing systems (not shown).

The CI symbol generator 5020 converts a predetermined number of inputdata symbols s_(n) into a plurality of CI code symbols w_(n). Thisconversion may involve summing information-modulated CI code chips. Afirst step in a CI symbol generation process involves generating codechips and/or acquiring code chips stored in memory or received from aninput data stream. In some applications, code chips may be generatedfrom a reduced set (e.g., an orthonormal basis) of code chips orvectors. Various methods for generating CI code chips are describedthroughout the specification. In some applications, code chips ororthonormal bases codes may be received over a communication link.

A second step in a CI symbol generation process involves impressing atleast one data symbol s_(n) onto at least one set of code chips. Thecode chips may be multiplied, phase shifted, modulated, or otherwiseimpressed with data symbol values s_(n). The code chips represent aphase space, such as a pulse position. Optionally, the code chips may beprovided with phase offsets with respect to some PAPR-minimizing code orencryption code.

A third step in a CI symbol generation process involves combining thecode chips to produce CI code symbols w_(n). FIG. 49 illustrates howrows of CI code chips are combined to produce CI code symbols w_(n).Predistortion may be performed by providing channel-compensation weightsto the CI code symbols w_(n).

The CI signal processor 5030 processes received CI symbols w′_(n) toproduce data-symbol estimates 4701′. A first step in a CI signalprocessing method includes generating code chips and/or acquiring codechips stored in memory or received from an input data stream. Code chipsmay be generated from a set of orthonormal codes or a subset of chipscomprising one or more orthonormal codes.

A second step in a CI signal processing method includes correlating atleast one vector of the code chips with a vector of the received datasymbols w′_(n). The correlation process may include a scalarmultiplication between the code-chip vector and the received data-symbolvector followed by integrating (e.g., summing) the products. Anotherembodiment of correlation includes adding together selected samples overa predetermined sample interval. Additional processing may be performedto produce estimates of the transmitted data symbols.

The CI signal processor 5030 may perform various types of combining,such as weighted combining as part of an MMSE, EGC, maximum likelihood,or any other measurement-based optimization process. The CI signalprocessor 5030 may perform channel compensation. The CI signal processor5030 may perform various receiver-processing functions, as describedthroughout the specification.

Overview of CI Channel Coding in a Multiple-Access System

In channel coding, a sequence of symbols from a first alphabet isrepresented by one or more symbols from a second alphabet. In general,an alphabet of order M=2^(N) is required to represent the M=2^(N)possible unique binary symbol sequences of N symbols each. A signalingsystem that represents an N-element binary symbol sequence using asymbol alphabet of order M=2^(N) is typically referred to as M-arysignaling. In M-ary signaling, the equivalent binary data rate R is thesymbol rate S multiplied by the number of bits per symbol N (i.e.,R=S*N). The number of bits per symbol N is log₂ M.

For each data symbol presented to a transmitter, the transmittergenerates a corresponding symbol waveform selected from a set ofdiscrete symbol waveforms. The symbol waveform is then transmitted overa communications channel to be received by at least one receiver. Eachtransmitted symbol waveform is subject to distortion and noise that canmake the received symbol waveform differ from the original transmittedsymbol waveform. Consequently, it is necessary to decide which symbol ofthe discrete set of known symbols was most likely transmitted. Thisdecision is performed in the receiver. The receiver output is a symbolsequence selected from the known set of symbols that represents the bestestimation of the transmitted symbol sequence.

The receiver synchronizes each received symbol waveform with a coherentintegration interval. In the absence of correct synchronization, thesymbol content of the received waveform can be misinterpreted.Synchronization can be lost due to multipath effects, such as fading andinter-symbol interference.

One approach that mitigates the effects of inter-symbol interference isto use M-ary orthogonal signaling with code waveforms that are a factorof log₂M times longer than each data symbol. Just as M-ary signalingwith an orthogonal modulation format (such as MFSK) improves theprobability-of-bit-error performance, waveform coding with anorthogonally constructed signal set, in combination with correlationdetection, provides the same improvement. Since the waveforms areorthogonal, each data symbol's waveform has no projection onto thewaveform of any other data symbol. If the symbol duration of the codewaveforms is much longer than the multipath delay spread, the effect ofthe multipath is reduced. Consequently, each data symbol is more easilydistinguished from other data symbols.

In one form of CI signaling, each data symbol is constructed from asuperposition of narrowband component waveforms. The superposition ofthe CI waveforms ensures orthogonality in the time domain with respectto other CI component-waveform sets that are phase shifted with respectto an integer-multiple shift of a full or half pulse duration. If theduration of the component waveforms is much longer than the multipathdelay spread, the effect of the multipath is reduced. CI waveforms canbe supplemented with an antipodal signal set to form a bi-orthogonalsignal set. Trans-orthogonal CI waveforms may be generated. CI waveformsmay be adjusted to provide the superposition signal with in-phase andquadrature-phase values, thus, enabling additional orthogonal waveformcodes.

Multiple-access coding uses one or more code orthogonality properties toseparate users. Certain types of channel coding can use one or more codeorthogonality properties to separate data symbols. Thus, coding used formultiple access (e.g., CIMA, CI/DS-CDMA, CI multiple-access codes, etc.)can also be used to encode data symbols and/or increase processing gainof a spread-spectrum system by increasing the effective duration of eachdata symbol. Furthermore, forms of CI coding may be combined withdirect-sequence coding and/or any type of channel coding. Suchcombinations may be made to produce various benefits, includingmulti-level coding, increased processing gain, improved channel coding,enhanced multiple access, and/or variable-rate communications.

CI codes used in higher-order signaling alphabets are more flexible thanconventional binary codes, such as Walsh codes, which are constrained tolengths of 2^(n). CI-coded data symbols may be co-modulated with a DSSSwaveform, CI-based waveform, or any other type of multicarrier,frequency-hopped, or chirped waveform. One objective of this type ofco-modulation is to effectively increase processing gain for a givendata rate without increasing the spread spectrum transmission bandwidth.Similarly, conventional coding techniques (such as DSSS, conventionalchannel coding, non-orthogonal signaling, Hadamard-Walsh coding, etc.)may be combined with CI-based waveforms (CI-TDMA, CI/DS-CDMA,CI/MC-CDMA, CI-OFDM, etc.) to increase the processing gain of a CI-basedcommunication system. Processing gain in a CI system is usually relatedto the number of carriers on which a data symbol is modulated, whereasfrequency diversity is related to the frequency band(s) in which CIcarriers are distributed. Processing gain may be provided with respectto time-domain (e.g., direct-sequence) encoding of the data symbol.

One preferred embodiment of the invention employs mutually orthogonalpolyphase CI waveforms that can be synchronously modulated upon aspread-spectrum code. All transitions of both the polyphase CI waveformsand the spread-spectrum waveforms occur simultaneously with a transitionof a common clock signal. The clock-signal frequency may be selected tosupport the finest possible pulse structure in each polyphase andspread-spectrum waveform. The finest pulse structure that can occur in awaveform determines the bandwidth of the waveform. Therefore, the clockrate establishes the bandwidth of the waveform. As long as a waveformsignal transition occurs at a clock edge, a multiplicative composite ofa polyphase CI and spread-spectrum waveform will not require additionalbandwidth beyond the bandwidth of its two constituent waveforms.Consequently, polyphase waveforms having a bandwidth less than or equalto the bandwidth of the DSSS waveform can be used without any increasein bandwidth of the polyphase/DSSS composite waveform.

In another preferred embodiment, the orthogonal signal set issupplemented with an antipodal signal set to form a bi-orthogonal signalset, further increasing the data rate achievable at a given DSSS or CIprocessing gain. Other embodiments include differential phase-shift key(DPSK) polyphase codes, CI-Walsh coding, differential CI-Walsh coding,coherent and/or non-coherent M-ary phase-shift keying combined withorthogonal polyphase and/or CI signaling within a single symbol; anddifferentially encoded coherent phase shift keying across two symbols,with orthogonal signaling within a symbol.

Although CI is commonly provided for multiple access, CI may also beused to encode data symbols. In another preferred embodiment, each of aplurality of data symbols is mapped into a weighted sequence of carrierwaveforms. Preferably, the weighted sequences are orthogonal orquasi-orthogonal to each other. The weighted sequence of subcarriers maybe MC-CDMA signals. Preferably, the weighted sequence includes asequence of CI signals. The weighted sequences may be furthercharacterized by a superposition of waveforms having a time-domainstructure similar to direct-sequence or polyphase signals. Thesuperposition of waveforms may be provided with a low PAPR.

FIG. 23A illustrates a time-domain relationship between each of aplurality of data symbols d₁, d₂, . . . , d_(m) and multiple-access orspread-spectrum code chips c₁, c₂, . . . , c_(N). The code chips areillustrated as shaped, overlapping chips. However the chips may benon-overlapping. Any form of chip shaping may be employed, such asraised cosine, sinc, and/or CI chip shaping. A k^(th) user modulateseach data symbol onto at least one period of its corresponding code. Thecode may be a binary code (e.g., a direct-sequence code) or a polyphasecode (e.g., a CI code). In addition to a multiple-access and/orspreading code, each data symbol may be encoded with a channel code.

FIG. 23B illustrates time-domain relationships between multiple userdata streams and associated orthogonal channel codes used to modulateeach symbol in each data stream. A k^(th) user transmits at least onedata symbol d_(mfk) (where m is a data-symbol number in a particularcode-period, f is a particular frame having a duration of at least onecode period, and k is a user number that references a particular user)on at least one chip sequence C_(mfk). The codes may be assigned withrespect to any number of parameters, including data-symbol number m,frame number f, and/or user number k. The channel code duration istypically the same as the multiple-access code duration. The channelcode bandwidth is typically less than or equal to the bandwidth of themultiple-access or spreading code C_(mfk). Channel codes may be derivedfrom the same set of codes used for multiple access. Each chip sequenceis shown as a plurality of time-domain chips c_(nmfk), where n indicatesa chip position relative to other chips in the code. Although the chipwaveforms are illustrated as overlapping waveforms, non-overlappingwaveforms may be employed. Any form of chip shaping may be provided,including, but not limited to, raised cosine, sinc, and/or CI chipshaping.

Each user may transmit data symbols in the same time interval by usingdifferent multiple-access codes. A single user may be provided with morethan one multiple-access code, thereby increasing the effectivebandwidth of that user's communication channel. A user may use adifferent multiple-access code and/or channel-code set relative to eachadjacent data symbol. A particular user may transmit multiple symbols ina given time interval by using multiple orthogonal channel codes. A usermay transmit multiple data bits per symbol by employing an M-arymodulation scheme, such as QAM, QPSK, etc.

FIG. 24 shows relative symbol durations between a user's data symbolsd₁, d₂, . . . , d_(m), channel-code symbols cc_(mn′) (where n′=1, 2, . .. , N′), and direct-sequence or CI-code symbols c₁, c₂, . . . , c_(N)for a channel code having a longer duration than the direct-sequence orCI code. A k^(th) user transmits one data symbol d_(m) corresponding toa particular channel code in one channel-code period. Multiple datasymbols d_(m) may be transmitted simultaneously by employing multiplesimultaneous channel codes. Each channel-code symbol cc_(mn′) has thesame duration as the direct-sequence or CI-code period. Each data symbold_(m) is spread over multiple direct-sequence or CI-code periods. Aparticular user may employ multiple direct-sequence and/or channel codesto increase throughput or reduce probability of error. In one embodimentof the invention, there is at least a one-to-one correspondence betweenchannel codes and data symbols. In another embodiment, data symbols,such as binary or M-ary data symbols, are impressed upon individualchannel codes. Similarly, multiple-access codes may comprise differentlevels of code granularity. For example, wideband codes may providespreading or inter-cell isolation, whereas relatively narrowband codesmay provide intra-cell orthogonality.

Although the channel-code symbols cc_(mn′) and the data symbols d_(m)are shown as rectangular symbols, these symbols may be shaped in thetime domain. For example, the symbols may be shaped with respect to someform of chip shaping, such as raised cosine, Gaussian, sinc, and/or CIchip shaping. The symbols may simply be tapered in the time domain.Frequency-domain windowing may be employed to provide a predeterminedtime-domain chip profile. Either or both the channel-code symbolscc_(mn′) and the data symbols d_(m) may convey M-ary signals, such aspolyphase, multi-magnitude, or hybrid signals.

FIG. 51 illustrates channel-code chips c_(nk) (where n indicates a chipposition relative to other chips in a code vector and k is a user numberthat references a particular user) and a data symbol d_(m) applied tomultiple carrier frequencies in a multiple-access system. Thechannel-code chips c_(nk) map at least one data symbol d_(m) to multiplefrequencies. The code vector may be a direct-sequence code, a CI code,or any other appropriate symbol alphabet.

In one set of embodiments of the invention, the channel-code chips havethe same duration as the data symbol d_(m). A multiple-access code usedherein preferably has the same code length (i.e., the same number ofcarriers). In one embodiment, frequency-domain multiple-access coding isprovided to the carrier frequencies as MC-CDMA, CIMA, or any otherfrequency-domain multiple-access coding. In another embodiment of theinvention, multiple-access coding is provided in the time domain in theform of direct-sequence coding, CI coding, and/or TDMA. In yet anotherembodiment of the invention, modulation on each carrier frequency ischaracterized by multi-tone CDMA or multicarrier direct-sequence CDMA.In another set of embodiments of the invention, multiple-access codingis characterized by CI/DS-CDMA and FIG. 33 indicates CI carriers for aparticular CI/DS-CDMA code or code chip.

Multiple channel codes may be used simultaneously as a means formultiple access or increased throughput. Data symbols may be encodedwith respect to an alphabet defined by the possible channel codes. Datasymbols may be encoded with respect to modulation of the channel codes.Data symbols may be encoded with respect to a combination of achannel-code alphabet and impressed modulation.

FIG. 52 illustrates an application of multi-level coding of the presentinvention. A plurality N′ of communication channels are indicated byfrequency-domain code vectors C₁=[c₁₁, c₁₂, . . . , c_(1N)] toC_(N′)=[c_(N′1), c_(N′2), . . . , c_(N′N)]. In a given time interval, adata symbol d_(m) may be transmitted on each channel. In one embodimentof the invention, at least one super-code vector C^(o)=[c^(o) ₁, . . . ,c^(o) _(M=N′)] is applied across the frequency-domain code vectors C₁ toC_(N′). Each frequency-domain code vector C_(n) is multiplied by asuper-code chip c^(o) _(m). Super-code vectors are preferably orthogonalor quasi-orthogonal with respect to each other. A particular super-codevector may correspond to a channel code or a multiple-access channel.Super codes may be changed relative to some predetermined time interval,such as the duration of a data symbol d_(m).

FIG. 53 illustrates a multi-level coding method of the invention thatspreads a data symbol d_(m) over multiple frequencies ƒ₀ to ƒ_(N−1) andtime intervals t. An n^(th) multiple-access channel or a channel code isdefined by a code vector C_(n)=[c_(n1), c_(n2), . . . , c_(nN)]. Thecode vector C_(n) may be an MC-CDMA code, a CI code, a CIMA code, etc. Asuper-code chip c^(o) _(m) from some super-code vector C^(o)=[c^(o) ₁, .. . , c^(o) _(M)] of length M multiplies the code vector C_(n) over somepredetermined time interval t. Preferably, the time interval t is someinteger multiple of the normal symbol duration T_(s)=1/ƒ_(s), whereƒ_(s) is the frequency separation between carrier frequencies. Thesuper-code vector C^(o) spreads a data symbol d_(m) over M timeintervals t. The super-code vector C_(o) is preferably one of a familyof orthogonal or quasi-orthogonal code vectors. In one embodiment of theinvention, each super-code vector may represent a particular datasymbol. In another embodiment of the invention, each super-code vectorrepresents a multiple-access channel.

FIG. 54A illustrates a method of sub-channel coding. Chips [c_(n1),c_(n2), . . . , c_(nN)] of at least one code C_(n) are provided to aplurality N of subchannels, such as spatial sub-channels. The codesequence C_(n) provides a data symbol or multiple-access channel withsub-channel (e.g., sub-space) diversity. If a small number of thesubchannels have poor link quality, the integrity of the coded datasymbol or channel is not significantly compromised. The effects ofinter-symbol interference can be reduced by a multicarrierimplementation, such as OFDM or some CI-based technique. Inter-symbolinterference may be mitigated by spreading and/or interleaving each datasymbol d_(m) in the time domain.

FIG. 54B shows a subchannel coding technique combined with time-domaincoding. Super codes C^(o) may be applied to orthogonal bases, such assubchannels, sub-channel codes, CI codes, direct-sequence codes, and/orany orthogonal or quasi-orthogonal diversity-parameter values. In thiscase, at least one super code C^(o) is applied to a particularsub-channel code C_(n) over multiple time intervals. The application ofthe super code C^(o) increases data symbol d_(m) duration.Alternatively, a super code C^(o) may be applied in the frequency domainto provide frequency diversity.

Super codes may provide channel coding and/or multiple-access coding.Although non-overlapping time intervals, frequencies, and subchannelsare illustrated in the preferred embodiments, coding for multiple accessand channel coding may be applied to any orthogonal or quasi-orthogonaldiversity-parameter values.

CI Channel Coding Systems

The following descriptions of transmitters and receivers adapted toperform CI channel coding reference functional diagrams that correspondto systems and methods of the invention.

FIG. 55 shows an embodiment of a transmitter adapted for combinedchannel coding and multiple access. A data source 5500 provides a streamof data bits to a symbol processor 5502. The symbol processor 5502groups the data symbols to generate a sequence of data words whereineach data word represents a symbol value. The symbol values may beprocessed via error-correction coding and/or interleaving by an optionalerror-correction coder 5504.

Error correction coding may be performed with Reed-Solomon codes, hybridReed-Solomon/binary codes, erasure codes, turbo codes, CI codes, etc.Error correction coding typically involves providing some sort ofparity-check symbols to the data symbols. Bi-orthogonal coding has theextra requirement of correcting the binary element of the data.Interleaving may be performed to reduce the problems associated witherror bursts. Error correction may be aided by changing thedirect-sequence code on each symbol in order to randomize the effect ofmultipath on each symbol. In several preferred embodiments, the effectsof multipath are mitigated by using CI. Either or both forward errorcorrection and automatic re-transmission request may be performed.

A coder (or CI coder) 5506 translates the input data into symbolwaveforms. The coder 5506 may modulate an appropriate phase changebetween the symbols. Modulation can take the form of minimum-shiftkeying or any other continuous-phase modulation. The coder 5506 mayincorporate coherent M-ary PSK or M-ary DPSK. The coder 5506 maytranslate the input data with respect to a stored set of waveforms. Thecoder 5506 may select a corresponding logic in a waveform generator (notshown). For bi-orthogonal or differentially bi-orthogonal coding, phaseinversion may be performed by complementing the symbol waveforms.

A frequency spreader 5512 combines the symbol waveform(s) with adirect-sequence or CI waveform generated by a DS/CI code generator 5510.The frequency spreader 5512 may include some sort of combining device,such as an exclusive OR logic gate or equivalent device. The output ofthe frequency spreader 5512 is processed by an RF modulator 5514 thatprovides an RF transmit signal that is optionally processed and coupledinto a communication channel by a transmitter 5516.

The order of modulation provided by modules 5510, 5512, and 5514 may bechanged. RF modulation 5514 may be implemented in stages and include IFprocessing and associated filtering. RF modulation 5514 may include anyform of direct conversion including frequency-conversion techniques ofthe present invention. Various modules may be coupled to the DS/CI codegenerator 5510. For example, the data source 5500, the error-correctioncoder 5504, and/or the coder 5506 may be coupled to the DS/CI codegenerator 5510 to impress data, error-correction coding, and/or channelcoding into the direct-sequence and/or CI codes generated by the DS/CIcode generator 5510.

FIG. 56 illustrates a receiver corresponding to one embodiment of theinvention. An input data sequence is provided to a correlator 5606. Asynchronizer 5602 controls the timing of various receiver components,including the correlator 5606, a multiple-access/spread-spectrumreference-code generator 5603, and a channel reference-code generator5604. Various implementations of the correlator 5606 may be provided.Optional components not shown in FIG. 56 may include time-tracking,synchronization-detection, level-control, a delay-lock loop, acomparator, and threshold detection-systems.

The synchronizer 5602 may include a matched filter, an aided-acquisitioncorrelator, and/or a threshold-detection circuit. Synchronizationtypically involves two primary steps. Acquisition involves bringing thespreading signals into coarse alignment. Tracking involves continuouslymaintaining optimal fine alignment via feedback.

A demodulator 5608 performs a maximum likelihood decision or some otherapproximation that determines which orthogonal waveform(s) was (were)transmitted. The correlator 5606 provides the demodulator 5608 with anumber M of correlation values corresponding to the M-ary signal inputto the correlator 5606. Any phase-shift data impressed upon theorthogonal waveforms can be demodulated by the demodulator 5608 viacomparison with at least one phase reference.

Demodulated data symbols are coupled to a data processor 5612. Afterdemodulation, each demodulated signal is decoded for errors iferror-correction coding is employed. The data symbols are then processedto form a bit stream. The data processor may include anoptimal-combining receiver, a multi-user detector, an interferencecanceller, a decision processor, and/or one or more feedback loops tocontrol receiver function in response to some performance measurement,such as BER, SNR, probability of error, received signal power, etc.

Systems and methods of the invention may be characterized by variousmodes of operation. Mutually orthogonal binary waveforms or other signalalphabets may be synchronously modulated onto one or more CI-basedsignals. Synchronous modulated implies that transitions of thechannel-code waveforms (i.e., the signal alphabets) and themultiple-access or spreading waveforms occur simultaneously. Thus,channel-code waveforms having a bandwidth less than or equal to thebandwidth of the multiple-access or spreading waveforms do not increasethe bandwidth of the composite waveform.

In one embodiment, orthogonal binary waveforms are modulated onto atleast one CI-code waveform. In another embodiment, orthogonal waveformsare modulated onto at least one signal having a CI-based sub-layer.Another set of embodiments includes modulating a signal set, such as oneor more orthogonal waveforms, onto a CI/DS-CDMA waveform.

Orthogonal or quasi-orthogonal CI codes may be synchronously modulatedonto one or more waveform sets. In one embodiment, at least one CI codeset or CI-encoded information signal is modulated onto a wave set of atleast one CI code. Another embodiment includes modulating CI-codedwaveforms onto any type of spread-spectrum or multiple-access waveform.One particular set of embodiments includes modulating at least oneCI-coded waveform onto at least one CI/DS-CDMA code set.

In one set of embodiments, the DS/CI code generator 5510 and themultiple-access/spread-spectrum reference-code generator 5603 areadapted to generate CI-based signals, such as CI codes or CI-basedmultiple-access signals. CI-based signals include CI/DS-CDMA signals,which can have binary or polyphase chip sequences. CI-based signals mayinclude any type of CI sub-carrier architecture, such as signalscharacterized by orthogonal circular (and/or elliptical) polarizations.In these embodiments, the coder 5506 and the channel reference codegenerator 5604 are adapted to generate one or more waveforms indicativeof a signal alphabet, such as a set of orthogonal, bi-orthogonal, ortrans-orthogonal waveforms. Waveforms generated by the coder 5506 mayinclude binary, polyphase, and or continuous-phase signals. The coder5506 may generate conventional channel codes that are then modulatedonto CI-based signals.

In another set of embodiments, the DS/CI code generator 5510 and themultiple-access/spread-spectrum reference-code generator 5603 areadapted to generate conventional spread-spectrum or multiple-accesswaveforms, such as any of various binary chip sequences. In theseembodiments, the coder 5506 and the channel reference code generator5604 are adapted to generate one or more CI-based signaling alphabets.CI-based signaling alphabets may include one or more CI codes. ACI-based alphabet may include any signaling alphabet constructed from asuperposition of CI signals.

A pulse-shaping filter may be provided to the DS/CI code generator 5510or the RF modulator 5514. The DS/CI code generator 5510 and themultiple-access/spread-spectrum reference-code generator 5603 may beadapted to provide a different code to each adjacent symbol in asequence of symbols. Error-correction coding may be employed to furtherreduce error rates. Coherent or non-coherent detection may be performedat the receiver.

CI Receiver Processing for Single-Carrier Signals

In one aspect of the invention, a received single-carrier ormulticarrier signal is decomposed into a plurality of orthogonal,overlapping carrier components. These components can then be processedto obtain benefits of parallel processing and frequency-domainprocessing. The selection of carrier components may depend on one ormore signal characteristics, channel characteristics, and/or receivercharacteristics. Methods and systems adapted to decompose a receivedsignal into CI components may be adapted to other embodiments andaspects of the invention described herein. For example, a widebandsingle-carrier signal may be decomposed into a plurality of narrowbandCI components to facilitate array processing.

Various embodiments of CI are characterized by a mapping processperformed by a receiver that maps time-domain samples of ahigh-bandwidth signal into a parallel set of low-bandwidth,long-duration symbols. FIG. 57A shows a frequency-domain profile 5701 ofa high-rate digital transmission represented by a time-domain profile5710 shown in FIG. 57B. The time-domain profile 5710 may be moreaccurately characterized by Gaussian or raised-cosine symbols.

The wideband signal spectrum 5701 may be decomposed into a plurality Nof narrowband signals 5702, as shown in FIG. 57C. However, if thenarrowband signals 5702 do not overlap in the frequency domain, some ofthe received signal energy (and thus, a substantial amount of theinformation) is lost. The lost signal energy is illustrated by aplurality of gaps 5703 between the narrowband signal spectrum 5702 andthe wideband signal spectrum 5701.

A preferred embodiment of the invention provides for decomposition of areceived signal into a plurality of overlapping narrowband carriersignals. FIG. 58A illustrates N modulated orthogonal carrier components.When a received signal is decomposed into carrier components, eachcarrier frequency ƒ_(n) is associated with a complex-valued symbolv_(n). In this case, a sample period T_(s)=1/ƒ_(s) provides overlappingfrequencies ƒ_(n) that are incrementally spaced with a frequencyseparation of ƒ_(s) between adjacent carriers.

The sample period T_(s) is a predetermined time interval in whichsamples are collected and processed, such as in a Fourier transformoperation. This duration T_(s) specifies a set of frequencies ƒ_(n) thatare orthogonal to each other. How the samples collected within eachsample period T_(s) are processed (e.g., selected and/or weighted)determines a receiver's sensitivity to particular frequencies.

Each carrier signal appears to be modulated with a complex data symbolv_(n) that is actually a complex-weighted superposition of a pluralityof data symbols Sm. Each symbol v_(n) has a symbol period ofT_(s)=1/ƒ_(s). A corresponding frequency spectrum in FIG. 58B shows theN frequency components. Depending on the particular embodiment of theinvention, the carriers may or may not be incrementally spaced infrequency. Subsets of the modulated carriers may or may not overlap. Ann^(th) symbol v_(n) corresponding to an n^(th) carrier frequency ƒ_(n),which results from a superposition of complex weighted w_(np) datasymbols s_(m), is expressed by:

v_(n)=Σ_(n,m=1)w_(nm)s_(m)

The vector representations v_(n) may be combined and processed usingmatrix operations to separate the data symbols s_(m). Appropriatetechniques involving any combination of estimation, optimization,interferometry, and/or cancellation may be used to separate the datasymbols s_(m).

FIG. 58C illustrates N′ modulated carrier components. In this case,N′>N. Thus, the frequency separation f′_(s) of the carriers is smallerthan ƒ_(s). Consequently, the symbol v_(n) period T′_(s) is longer thanT_(s). The frequency separation f′_(s) and the symbol period T′_(s) areexpressed by the following equations:

f′s=ƒ _(s) N/N′

T′ _(s) =T _(s) N′/N

A frequency-domain spectrum of the carrier components shown in FIG. 58Cis shown in FIG. 58D.

A transmission method of the invention provides a transmitter with amulticarrier signal having selected frequency components intended tofacilitate separation and processing of the received data symbols. Onthe receive side, factors that may play a part in selecting carrierfrequencies as part of a decomposition process include number ofparallel operations, duration and frequency of sampling, andtransformation characteristics between transmitted symbols u_(p) andreceived carrier symbols v_(n).

FIG. 58E exemplifies a spectral profile selected for a particularcommunication channel. Information signals are transmitted and/orreceived in a plurality of spectral ranges 5811, 5813, 5815, and 5817.The following spectral ranges are avoided: a spectral range 5812allocated to another user, application, or system, a spectral range 5814experiencing a deep fade, and a spectral range 5816 experiencing jammingor interference. A transmitter may be adapted to avoid transmitting inundesirable spectral ranges. A receiver may be adapted to avoidreceiving signals in undesirable spectral ranges. In either case, thedesired spectral ranges may be decomposed into CI carriers.

FIG. 59A illustrates a method of generating CI carriers as part of atransmission process. A channel-estimation step 5901 characterizes thecommunication channel and identifies desirable and undesirable spectralregions. Channel estimation may be performed with respect to multiplechannels. Channel estimation may be performed with signals received fromremote transceivers. Alternatively, remote transceivers may performchannel estimation and communicate those estimates to the localtransceiver.

CI carriers are generated in a CI carrier generation step 5905 based onchannel estimates. Pre-transmission processing 5906 is performed priorto transmitting 5907 the carriers into a communication channel.Pre-transmission processing 5906 may include predistortion, A/Dconversion, modulation, multiplexing, multiple-access processing, upconversion, amplification, filtering, coding, beam forming, etc.

FIG. 59B illustrates a method of generating CI carriers as part of areceiving process. A channel-estimation step 5901 characterizes thecommunication channel and identifies desirable and undesirable spectralregions. Channel estimation may be performed with respect to multiplechannels. Channel estimation may be performed with the aid of signalsreceived from remote transceivers. Alternatively remote transceivers mayperform channel estimates and communicate those estimates to the localtransceiver.

A received signal is decomposed 5904 into a plurality of CI carriers.Carrier properties, such as frequency selection, frequency spacing, andcomplex weighting are selected, at least in part, with respect to thechannel estimates. Optionally, the carriers may be processed beforebeing combined in a combining process 5906. The combining process 5906may be directed by channel estimates. Combining 5906 may be performedusing any appropriate optimal-combining technique, such as MMSEcombining. Alternatively, other combining techniques may be used. Thecombined signals are then conveyed to a receiving process 5908 that mayfurther process the combined signals.

Decomposition of a received signal into narrowband CI components permitslow-speed, parallel processing. In addition to simplifying demodulationof a high-rate signal, CI carrier processing can simplify manydata-processing applications (such as error detection, error correction,virus detection, verification, decoding, and/or other securityprotocols) that typically require high-rate processing. Thissimplification is enabled by slower data-processing requirements. Thecombining of multiple low-speed processes produces high aggregate datarates. Similar benefits can be provided to other signal-processingoperations, such as interference mitigation, noise mitigation,correlation, matched filtering, coding/decoding, beam forming, etc.

FIG. 60A illustrates a CI receiver adapted to process receivedsingle-carrier signals. Single-carrier signals include a single carriersignal modulated with an information signal, a single unmodulatedcarrier, and/or any received multicarrier signal that can be processedas a single-carrier signal.

A single-carrier receiver of the invention includes anorthogonal-frequency filter 6001 coupled to an optimal combiner 6002.Additional signal-processing units (not shown), such as one or moredecoders, formatters, beam formers, demodulators, demultiplexers,despreaders, channel compensators, etc., may be coupled to the combiner6002. The orthogonal-frequency filter 6001 shown in FIG. 60A includes anoptional filter 6010, a sampler 6011, and a digital filter 6012, such asa Fourier transform processor.

The orthogonal-frequency filter 6001 is adapted to receive at least oneinput single-carrier and/or multicarrier signal. The input signal may beprocessed prior to being coupled into the orthogonal-frequency filter6001. For example, a signal received by a receiver system (not shown)coupled to a communication channel (not shown) may be amplified,filtered, demultiplexed, demodulated, modulated, and/or down convertedprior to being coupled into the orthogonal-frequency filter 6001.Optionally, the receiver system (not shown) may perform beam forming,interference cancellation, despreading, demultiplexing, channelcompensation, multiple-access processing, A/D processing, and/or D/Aprocessing.

The input single-carrier signal may optionally be processed by thefilter 6010. The filter 6010 may include a passband filter, such as toprovide anti-aliasing. The filter 6010 may include one or more filters,such as low-pass, high-pass, and/or notch filters. The filter 6010 maybe adapted to select one or more communication channels, rejectinterference, compensate for channel distortion, and/or avoid deepfades.

The sampler 6011 performs digital sampling. A sampler, such as thesampler 6011, may include one or sample-parameter controllers (notshown) to select and/or adapt sample parameters, such as sample rate,sample width, sample duration, sample interval, sample shape, and/orsample weights. The sampler 6011 may optionally be integrated into afilter, such as the digital filter 6012. The selection and/or adaptationof various sample parameters can be performed to affect the frequencyresponse of the orthogonal-frequency filter 6001. Furthermore, thesampler 6011 may optionally include a digital filter (not shown) toprovide a predetermined frequency response.

One advantage of a digital receiver system includes the ability to adaptthe sample rate to operate over a wide range of data rates. Anadjustable anti-aliasing filter combined with an adjustable-rate samplermay be provided to appropriately process a wide range of input signalbandwidths. Alternatively, a fixed sample rate and static analog filtermay be combined with a digital system adapted to use multi-rate signalprocessing algorithms to accommodate a predetermined range of signalbandwidths and sample rates.

The sampler 6011 may include one or more samplers. Samples may be storedin a storage system (not shown). Samples may be processed (e.g.,selected, weighted) prior to, or following storage. The sampler 6011 mayinclude one or more quantizers (not shown), such as noise-rejectingquantizers.

The digital filter 6012 may include one or more filters to processsamples produced by the sampler 6011. The filter 6012 may include afilter bank. The filter 6012 may include any type of signal processoradapted to perform a Fourier transform operation. For example, thefilter 6012 may perform one or more FFTs, DFTs, and/or OFFTs. The filter6012 may include one or more filters with simple delays and/orsophisticated filters having complex amplitude and phase responses.

FIG. 60B illustrates a CI receiver embodiment adapted to processreceived single-carrier signals. The single-carrier receiver includes anorthogonal-frequency filter 6001 coupled to an optimal combiner 6002.The orthogonal-frequency filter may 6001 include one or more optionalanalog filters 6010.1 to 6010.N, one or more samplers 6011.1 to 6011.N,and one or more integrators 6012.1 to 6012.N. The numbers of analogfilters 6010.1 to 6010.N, samplers 6011.1 to 6011.N and integrators6012.1 to 6012.N may differ from each other.

The analog filter(s) 6010.1 to 6010.N may select one or more frequencychannels. Similarly, the sampler(s) 6011.1 to 6011.N, and/orintegrator(s) 6012.1 to 6012.N may select one or more frequencychannels. A plurality of samplers may be coupled to a single analogfilter. A plurality of samplers, such as samplers 6011.1 to 6011.N, maybe provided by a single sampler that collects samples and a selector(not shown) that selects collected samples to provide different samplesrates and/or sample intervals. The integrators 6012.1 to 6012.N mayinclude combiners (e.g., adders), accumulators, and/or storage devices.

FIG. 61 illustrates basic components of a repeater that converts areceived signal into overlapping, orthogonal CI components, processesthe components, and recombines the processed components prior totransmitting the combined components. The repeater includes anorthogonal-frequency filter 6101, a sub-carrier processor 6102, and aninverse orthogonal-frequency filter 6103.

The orthogonal-frequency filter 6101 is a filter that is adapted todecompose a received signal into a plurality of CI components. Thefilter 6101 may down convert the received signal into one or morebaseband and/or IF signals. Various methods of down conversion may beperformed, such as mixing, passband sampling, or any appropriatezero-intermediate-frequency process. The down-converted signals may beconverted to digital signals in an A/D process prior to, during, orfollowing down conversion. The sub-carrier processor 6102 may be adaptedto filter one or more CI components, or otherwise mitigate noise and/orinterference. The processor 6102 may perform channel compensation oftransmitted and/or received signals. The processor 6102 may performpre-distortion processing. The processor 6102 may be adapted to performvarious data-processing applications.

The inverse orthogonal-frequency filter 6103 may be adapted to combinethe processed signals prior to transmitting the signals into acommunication channel (not shown). The filter 6103 optionally performsamplification. The filter 6103 may include an up sampler, an inverseFourier transform, an up converter, a filter bank (such as areconstruction filter bank), an amplifier, a D/A converter, anarray-processing system, and/or any other appropriate pre-transmissionsystem or device.

FIG. 62 illustrates basic components of a CI receiver coupled to aplurality of array elements 6200. The array elements 6200 may includeone or more RF processors (not shown) adapted to perform RF-signalprocessing, such as amplification and filtering. An orthogonal-frequencyfilter bank (OFFB) 6201 is adapted to separate one or moresingle-carrier signals generated by the array 6200 into a plurality ofCI carriers. A CI carrier may be a modulated carrier signal or a complexvalue related to at least one information signal value in a particularCI carrier band. One or more filters in the OFFB 6201 may be coupled toeach element of the array 6200. The OFFB 6201 may be adapted to performtypical front-end processes, such as, but not limited to, A/Dconversion, down conversion, demodulation, and channel selection.

Various signal processing functions may be applied to the CI carriersignals in an optional processor 6202. These processes may include oneor more of the following; channel compensation, interference mitigation,carrier weighting, multi-user detection, demodulation, demultiplexing,despreading, A/D conversion, down conversion, beam forming,interferometry, matched filtering, convolution, and decoding. The CIcomponents are combined in a combiner 6203. The combiner 6203 mayperform one or more types of signal combining, including optimalcombining.

FIG. 63 illustrates basic components of a matched-filter CI receiveradapted to process received single-carrier signals. Receivedsingle-carrier signals are processed in a down converter 6301.Down-converted signals are digitized in an A/D converter 6302 prior tobeing processed in an OFFB, such as an FFT 6303. In some applications,the A/D converter 6302 and the down converter 6301 may be embodied by ananti-aliasing filter (not shown) and a passband sampler (not shown).

The FFT 6303 separates the received single-carrier signal into aplurality of CI component signals that are correlated with a pluralityof reference component signals. A CI reference generator 6310 generatesthe reference component signals and provides the signals to a correlator6304. The correlator 6304 output may be coupled to one or moreadditional signal processing systems (not shown).

An embodiment of the CI reference generator 6310 includes asingle-carrier reference-signal generator 6311 coupled to an OFFB, suchas an FFT 6312. The FFT 6312 separates the single-carrier reference intoa plurality of reference component signals.

The correlator 6304 may include a plurality of matched filters (notshown) adapted to process each CI component signal/reference componentsignal pair. In one embodiment, the FFT 6303 may be provided with aprocessor (such as the processor 6202 shown in FIG. 62) to compensatefor channel effects and/or interference. In an alternative embodiment, aprocessor and a combiner (such as the processor 6202 and the combiner6203 shown in FIG. 62) are coupled between the FFT 6303 and thecorrelator 6304, and the CI reference generator 6310 is adapted togenerate a single-carrier reference signal. The correlator 6304 isadapted to correlate the processed and combined received signal with thereference signal.

FIG. 64A illustrates a CI receiving method adapted to process asingle-carrier signal. Received signals are optionally down converted6401 to one or more baseband or IF signals. Down conversion 6401 mayinclude anti-aliasing filtering and passband sampling. Down conversion6401 may include selecting and/or adjusting sample widths and/orintegration times. Down-converted signals may optionally be filtered6402. Filtering 6402 may include channel selection.

A received single-carrier analog signal is converted to a digital signalin an A/D conversion step 6403. The digital samples are provided to anOFFB step 6404 that separates the digital signal into a plurality of CIcarriers or CI-carrier values. The carriers or carrier values areoptionally processed in a processing step 6405 before being combined ina combining step 6406. Processing 6405 and combining 6406 may becharacterized by optimal combining. The processing step 6405 may includeone or more of the following; channel compensation, interferencemitigation, noise mitigation, weighting, multi-user detection,demodulation, demultiplexing, despreading, A/D conversion, downconversion, beam forming, interferometry, matched filtering,convolution, and decoding.

FIG. 64B illustrates basic steps of a CI reception method. A receivedsingle-carrier signal is decomposed into a plurality of CI components ina decomposition step 6410. The received signal may be an analog or adigital signal. An analog signal is typically decomposed into amulticarrier analog signal or a plurality of complex values representingcarrier values. A digital signal may be decomposed into a plurality ofanalog carriers whose superposition represents time-domaincharacteristics of the digital signal. The received signal may be amulticarrier signal. However, the decomposed carriers do not need tocorrespond to the received carriers.

The decomposed signal components may be processed in an optionalprocessing step 6411 prior to combining 6412. Various processing andcombining steps may be performed, as described throughout thespecification.

FIG. 64C illustrates basic steps performed by a CI receiver. Channelestimation 6420 is performed using blind adaptive techniques and/ortraining signals. Channel selection 6421 is performed based on channelestimation and/or multiple-access considerations. Received signals aredecomposed 6422 into CI component signals, which may optionally beprocessed in one or more processing steps 6423. The CI componentssignals are combined in a combining step 6424.

Software-Defined Implementation of CI Systems

The primary issue facing the wireless communication industries is how touse the available spectrum most efficiently given current channelconditions and user demands. Existing wireless systems do not addressthis issue effectively because the physical-layer functionality is fixedwhile channel conditions and network traffic can change rapidly.

Recently, the concept of an adaptable network based on software-definedtransceivers has been introduced. However, the implementation of thisconcept has been limited by conventional technologies. Currently,software-defined radio is limited to unsophisticated switching schemesbetween dedicated hardware components, thus, providing only a primitiveform of interoperability between only two or three transmissionprotocols.

One of the goals of software-defined networks is to enable a moredynamic organization of resources. In order to achieve this goal,software radio should enable dynamic adaptations of all communicationlayers, including the physical layer, which is typically implemented inhardware. As a result of the limitations of conventional radiotechnologies, prior-art software radio development is directed primarilytoward interoperability problems resulting from different cellularstandards. The implementation of CI-based technologies provides theadaptability and low complexity necessary to implement asoftware-defined solution for wireless networking.

CI systems and methods described herein have applicability to wirelessand guided-wave systems including, but not limited to, base stations,mobile transceivers, fixed subscriber units, routers, gateways, patches,and repeaters. Adaptable CI implementations of the invention may includeproviding communication between devices that utilize differenttransmission standards. CI systems may provide associated controloperations, such as identifying a particular transmission protocol usedby a particular device, reserving channels for transmission, monitoringchannel use (including channel reservation and channel release),requesting data transmissions and/or state information from remotedevices, attaching tags to data streams for identification and/or accesscontrol, and providing instructions to remote transceivers to adjust orcontrol processing, transmit status information, and/or identification.

A CI-based software radio can extend adaptive link-layer techniques tothe physical layer. This enables more efficient use of the spectrum bydynamically adjusting physical-layer characteristics to current channelconditions, network traffic, and application requirements. CI cansignificantly improve wireless network performance and functionality byadapting to different requirements for bandwidth, error rate, latency,link priority, and security.

Embodiments of a CI-based communication system may include interactivecapabilities between the physical layer and higher layers such that aresponse to changing conditions and operational requirements can bedirected to an appropriate physical-layer function. For example, a basestation in a mobile wireless network can dynamically create channelsdepending on the number of mobile units in its coverage area and theirservice requirements. When additional units enter the area, systembandwidth can be assigned accordingly.

In ad-hoc networks, base station functions (e.g., routing, powercontrol, synchronization, geo-location services, etc.) may bedistributed among subscribers and repeaters. CI is an ideal technologyfor mitigating multipath effects, which can be particularly sever inad-hoc networking environments. The performance benefits of CI can beused to greatly reduce subscriber-unit emissions for those units thatperform routing and relay functions. CI can also be used to adaptbase-station and access-point functions to maintain link quality andperform load balancing (e.g., managing power budgets for devices actingas routers and relays, managing system spectrum allocations, andadjusting cell boundaries to adapt to changing user demands, powerbudgets, and spectrum use.

Bandwidth can be dynamically allocated to up-stream and down-streamchannels depending on network traffic characteristics. Units requiringreal-time or broadband services may be assigned to dedicated channels,whereas units having bursty data requirements may be assigned to ashared channel.

The proposed CI network adjusts time-domain and frequency-domaincharacteristics of transmissions by applying weights to the CI carriers.Thus, CI carriers can be processed to produce signals having variousphysical-layer characteristics:

Multiple-access protocols (e.g., DS-CDMA, TDMA, OFDM, MC-CDMA)

Channel codes

Modulation types (e.g., phase modulation, frequency modulation,amplitude modulation, time-offset modulation, etc.) and modulationlevels (e.g., binary, M-ary)

Multiplexing (e.g., TDM, FDM, CDM)

Formatting (e.g., frame length, headers, payload length, etc.)

Source coding

Frequency agility (e.g., frequency hopping, variable aggregatebandwidth, frequency selectability, etc.)

Conventional software-based radios can provide adaptability to differentcommunication standards. However, conventional software-based systemshave the associated complexity of performing many physical-layer andrelated processes via separate functional processes. This complexitynecessitates multiple processors, resulting in greater system cost andcomplexity than conventional hardware-based systems.

Alternatively, a CI-based software-defined radio simultaneously performsmany processing functions via sub-carrier selection and weighting. Theselection of CI carrier frequencies and the application of weightsconsolidates many of the physical-layer processes, which are typicallyperformed in multiple stages using different signal-processingtechniques.

FIG. 65 illustrates how basic physical-layer functions can be combinedinto three processes: CI carrier and weight calculation 6511, CI carrierselection 6512, and CI carrier weighting 6513. A selection ofappropriate carriers and the application of carrier weights can providebasic physical-layer transceiver processes, such as formatting andsource coding 6501, encryption 6502, channel selection 6503, channelcoding 6504, multiplexing 6505, modulation 6506, spread-spectrumprocessing 6507, and multiple-access processing 6508. In one set ofembodiments, the physical-layer processes are performed viasoftware-controlled processes. Optionally, A/D conversion 6509 andfrequency conversion 6510 may be performed via harmonic and/orsub-harmonic processes 6515. A/D conversion 6509 may be integrated intofrequency conversion 6510 and/or Fourier processes 6514.

CI-based systems process wideband signals as a superposition ofnarrowband signals. In addition to enabling slow, parallel processing,which facilitates the implementation of software-based processing andsimplifies the required microprocessor architecture, a CI transmittercan process carriers to improve performance in the following ways:

Apply pre-distortion weights to compensate for multipath fading.

Eliminate carriers having deep fades and/or high interference.

Adapt to different spectrum allocations.

Operate across non-contiguous frequency bands.

Achieve wideband frequency-diversity benefits for a narrowband datachannel.

Similarly, a receiver can process received CI carriers in the followingways to achieve various performance and system benefits:

Apply post-distortion weights to compensate for multipath fading.

Disregard carrier frequencies having deep fades and interference.

Filter noise and/or interference on each carrier.

Perform multi-user detection to mitigate interference.

Perform space-frequency processing to achieve spatial diversity and/orenhance bandwidth efficiency.

Various sub-layer processes may be implemented in software. This enablesa CI-based system to be reprogrammed such that various processingfunctions (e.g., pulse shaping, sub-carrier selection, sub-carrierweighting, coding, modulation, power control, spatial processing,multiplexing, multiple access, combining, decision, feedback, processcontrol, etc.) can be adapted to different applications and systemrequirements.

FIG. 66 illustrates an embodiment of a CI-based software-defined radio.A software implementation of a CI-based transceiver may include one ormore signal processing hardware components 6603.1 to 6603.j and one ormore CI-based signal processing software components 6601.1 to 6601.i.The software components 6601.1 to 6601.i may reside on one or more ofthe hardware components 6603.1 to 6603.j or on one or more additionalhardware components that are not shown. For example, the softwarecomponents 6601.1 to 6601.i may reside on a computer main frame or aworkstation. At least one of the hardware components 6603.1 to 6603.jmay be coupled to at least one of the software components 6601.1 to6601.i by at least one interface 6602. The interface 66021 mayoptionally couple together hardware and/or software components.

The software components 6601.1 to 6601.i may include at least one localand/or remote computer program adapted to process signals received fromthe hardware components 6603.1 to 6603 j. The software components 6601.1to 6601.i may include one or more application programs for performingdigital signal processing. One or more software components 6601.1 to6601.i may provide control signals to one or more hardware components6603.1 to 6603.j to select, adapt, or alter signal processing. Theinterface 6602 may include a bus or network (not shown). The interface6602 may include one or more radio interfaces.

The hardware component(s) 6603.1 to 6603.j typically include atransmitter and/or receiver system, and a storage medium (e.g., diskdrive, tape drive, CR Rom, DVD, flash memory, or any other storagedevice) for storing application programs and data. Hardware and/or thesoftware may perform A/D conversion, as necessary. In some applications,modulation and/or demodulation may be performed digitally with anycombination of software 6601.1 to 6601.i and hardware 6603.1 to 6603 jcomponents.

In one set of embodiments of the invention, control signals are providedto the hardware components 6603.1 to 6603.j over one or morecommunication channels normally processed by the software radio. Forexample, a software component (such as at least one of the softwarecomponents 6601.1 to 6601.i) residing at a remote receiver location mayreceive signals transmitted by the radio, process the received signals,and convey some control information in the data stream (e.g., in aheader or pilot channel) to the hardware components 6603.1 to 6603.j.Much of the signal processing in a radio network may be performed by asingle processing system (such as a base station) to reduce the cost andcomplexity of mobile transceivers. Alternatively, signal-processingoperations may be distributed throughout the network in a way thatbalances processing and/or communication-resource (e.g., spectrum use)loads.

One or more software components 6601.1 to 6601.i may be replaced toprovide different signal processing and/or control features. In anotherset of embodiments of the invention, software is uploaded to a remotetransceiver via one or more communication channels normally processed bythe software radio. This simplifies software updates and enhancessignal-processing versatility of the network.

Conventional software-based radios can provide adaptability to differentcommunication standards. However, conventional software-based systemshave the associated complexity of performing many physical-layer andrelated processes via separate functional processes. This complexity cannecessitate multiple processors, resulting in greater system cost andcomplexity than conventional, substantially hardware-based, systems.

Alternatively, CI-based software-defined radio simultaneously performsmany processing functions via sub-carrier selection and weighting.CI-based protocols greatly exceed the performance (e.g., throughput,system capacity, bandwidth efficiency, power efficiency, probability oferror, interference mitigation, and range) of any conventional softwareradio while enabling backward compatibility with all conventionaltransmission and multiple-access protocols. Furthermore, CI provides aframework to migrate all transmission protocols to a commonhigh-performance platform that is suitable for all applications.

FIG. 67 illustrates basic baseband-processing components of a CItransceiver. A transmit data stream is processed by anencoder/interleaver system 6710 that provides parallel data streams toan IFFT processor 6711. In-phase and quadrature-phase transmit signalsare generated by either the IFFT processor 6711 or one or moresubsequent signal-processing systems (not shown).

Received data signals are separated into sub-carrier components by anFFT processor 6721. Sub-carrier values are combined by a combiningsystem 6722 prior to being decoded in a decoder/de-interleaver system6723. Various control signals may be generated throughout the receiverprocessing operations. For example, performance measurements (e.g., BER,SNR, SNIR, etc.) of received data symbols may be used to adjust variousoperations, such as combining. Received data symbols may be used toadjust gain control of either or both of the transmit side and thereceive side of the transceiver. The combining system 6722 may generatecontrol signals to adjust the function of the encoder/interleaver system6710 and/or the decoder/de-interleaver system 6723. Similarly, othercontrol schemes that are well known in the art may be performed by thetransceiver.

In a CI transceiver, the combiner 6722 may analyze one or more signalcharacteristics (e.g., bit rate, modulation type, modulationcharacteristics, symbol constellation, processing gain, anddirectionality), one or more link characteristics (e.g., priority,security requirements, quality of service requirements, applicationrequirements, information type, spectrum use, channel separation,coverage, and network topology), and/or one or more signal measurements(e.g., SNR, SNIR, probability of error, BER, soft decisions, signalpower, Doppler effects, phase jitter, channel estimation, andsynchronization). Based on this analysis, the combiner 6722 may beadapted to select and/or adapt one or more transceiver systems and/orfunctions described throughout the specification. Various processingcharacteristics that the combiner 6722 may select and/or adapt includefilter parameters, channel selection, interference filtering, channelcompensation, sample rates, sample widths, number of samples per sampleinterval, sample-interval duration, sample selection, sample grouping,decimation, quantization, synchronization, local oscillator amplitude,reference signal phase, gain, detector threshold, constellation,processing gain, modulation, demodulation, multiplexing, demultiplexing,multi-user detection, multiple access, formatting, source coding, beamforming, null steering, interferometry, combining technique, waveformshaping, coding, and/or system resource allocation (e.g., CPU use,memory, spectrum, power, etc.).

Software may be used to adapt the basic baseband-processing componentsto constraints imposed by the propagation environment, network load,quality of service, link priorities, differentiated securityrequirements, spectrum-use regulations, power constraints, latencyrequirements, interference, and jamming. Furthermore, thebaseband-processing components shown in FIG. 67 may be adapted toprovide additional processing functions, such as up conversion, downconversion, and demodulation.

In CI-based systems, as well as in software radio, modulation parameters(e.g., type of modulation, modulation level, etc.) may be adjusted withrespect to one or more constraints, such as bandwidth efficiency,probability of error, latency per bit, and power consumption. Coding maybe controlled with respect to similar parameters including probabilitiesfor detected and/or undetected errors. Code control may includeselecting and/or adjusting any combination of code types, individualcodes, code lengths, code generation, and decoding. A unique aspect ofCI is that it enables modulation and coding-related constraints to beaddressed via sub-carrier selection and weighting, thus, reducing orobviating the need for adjusting modulation and coding parameters.

FIG. 68 illustrates transmission methods 6810 and reception methods 6820of the present invention. Steps within the methods 6810 and 6820 can beregarded as functional blocks or systems within a CI transceiver.Various systems and methods not shown are implied. For example, varioussteps and components may be synchronized. Synchronization may includeopen loop and/or closed loop transmitter synchronization. Phasesynchronization may be performed via phase-locked loops. Synchronizationcan include carrier synchronization, sub-carrier synchronization, symbolsynchronization, frame synchronization, and/or network synchronization.Filtering, amplification, as well as other signal-processing steps andsystems may be included within the steps shown in FIG. 68.

Signals from an information source (not shown) are provided to aformatting step 6801 followed by a source-encoding step 6802. Encodedsignals are encrypted 6803 and provided with channel coding 6804 beforebeing multiplexed 6805. A modulation step 6806 is performed beforespreading 6807 and multiple-access processing 6808. A transmission step6809 processes and transmits the resulting signals into a communicationchannel 99.

Transmitted signals are coupled out of the channel 99 in a receptionstep 6819. The received signals are processed in a multiple-access step6818. The signals are despread 6817, demodulated 6816, and demultiplexed6815 prior to channel decoding 6814. The decoded signals are decryptedand processed in source decoding and formatting steps 6812 and 6811before being coupled to an information sink (not shown).

In one set of embodiments, at least some of the steps illustrated inFIG. 68 and their corresponding system components can be combined. Inother set of embodiments, one or more of the steps and correspondingsystem components may be omitted. For example, essential transmittingsteps include formatting 6801, modulation 6806, and transmission 6809.Essential receiving steps include reception 6819, demodulation 6816, andformatting 6811. All other steps shown in FIG. 68 are optional.

The formatting step 6801 may process a source signal (e.g., data, amessage, an information signal) to make it compatible with digitalsignal processing. Data, a message, or an information signal describes asignal whose spectrum extends from (or near) d.c. up to a finite value.This is also referred to as a baseband or low-pass signal.

FIG. 69A illustrates how digital, text, and analog signals are formattedfor different information signals. Digital information is typicallypassed through to a waveform-encoding step 6824. However, in someapplications, digital information may be reformatted. Text informationis first encoded into a sequence of bits in an encoding step 6823.Groups of k bits may be combined to form symbols from an alphabet ofM=2^(k) symbols.

An analog signal is sampled in a sampling step 6821 to produce adiscrete pulse-amplitude-modulated waveform. Sampling 6821 can includeimpulse sampling, natural sampling, sample and hold, over sampling,under sampling, as well as any other form of sampling. Preferably,sampling 6821 is provided as part of a CI-based method or system. Forexample, CI sampling, orthogonal frequency Fourier transforms, and/orother CI-based procedures or components may include at least onesampling method or system. An anti-aliasing filter (not shown) may beprovided prior to sampling. Post filtering may be performed followingsampling 6821 to remove aliased signal components. The sampled signal ispassed to a quantizer 6822 prior to being coded 6823.

Pulse-code modulated (PCM) symbols may be generated from quantized pulseamplitude modulated signals. Analog signals are sampled and uniformly ornon-uniformly quantized to one of L levels. Each quantized sample isthen digitally encoded into a length log₂L codeword. PCM waveform typesinclude non-return-to-zero, return-to-zero, phase-coded, and multi-levelbinary. Different waveform types within each PCM classification, as wellas other PCM waveform types, may be generated by providing appropriateweights to CI carriers. Similarly, multi-level signals may be generatedby appropriate CI-carrier weighting.

Pulse-shape selection is typically based on various parameters,including spectral characteristics, feasibility of synchronization,interference and noise immunity, and implementation costs andcomplexities. Various pulse shapes, including raised cosine, sinc, etc.,can be provided by appropriately weighting CI carriers. Roll-off factorscan be controlled by adjusting CI carrier weights. Uniformly weighted CIcarriers result in a sinc-like function. Various windowing techniquesmay be used to generate CI superpositions having predeterminedtime-domain characteristics.

Pulse overlapping may be performed, such as to generate substantiallyorthogonal symbol positions, information-channel positions, and/ormultiple-access channels. Pulse overlapping may be performed viaappropriate CI carrier weighting. Pulse overlapping may also beperformed via suitable time-domain delay and overlapping methods.Although pulse overlapping is shown with respect to CI signals, anypulse shapes may be overlapped. Furthermore, pulse shapes may beadjusted to reduce interference between overlapping pulse shapes.

Source coding 6802 forms efficient descriptions of information sourcesthat improve the SNR for a given bit rate or improve the bit raterelative to a given SNR. Source coding can include differential pulsecode modulation, block coding, synthesis/analysis coding, and/orredundancy-reducing coding. CI can easily be integrated into all typesof coding. CI also provides diversity benefits that reduce signaldegradation due to noise, interference, and distortion. CI diversitybenefits can simultaneously enhance throughput and SNR. CI codes includemulticarrier-based direct-sequence CI codes, polyphase CI codes,poly-amplitude CI codes, or any combination thereof.

The encryption step 6803 provides link privacy and user authentication.Various data-encryption techniques may be integrated into a CI carrierweighting process. Furthermore, various physical-layer encryptiontechniques may be used. For example, DSSS and FHSS can provide somesecurity while enabling processing gain and multiple access. CIdirect-sequence and frequency-hopping code security may be enhanced byadjusting code sequences, code lengths, or a combination of physicalsignal parameters and/or processes used to encode and/or encryptinformation.

Diffusion describes a process of smoothing out statistical fluctuationsin a transmission signal. For example, the pseudo-random nature of somedirect-sequence codes provide a Gaussian-like energy distribution in thefrequency domain. CI may be used to effect diffusion by minimizing PAPR,enabling high processing gains, and lowering spectral power densities byspreading information signals across non-contiguous frequency bands.

Channel coding 6804 improves communication link performance by enablingthe transmitted signals to better withstand the effects of variouschannel impairments, such as fading, noise, and interference. Channelcoding 6804 may include channel estimation, which can be performed byprocessing the complex carrier amplitudes of received CI signals.Channel coding 6804 may be implemented by applying appropriate weightsto CI carriers to generate predetermined time domain channel codes.Similarly, CI carrier weighting may be performed to generate signalshaving other predetermined diversity-parameter characteristics.

Waveform coding may utilize CI codes. For example, waveform codes mayinclude orthogonal and/or bi-orthogonal CI codes. Similarly,trans-orthogonal or simplex CI codes may be used. CI coding may also becombined with higher-order (M-ary) modulation to provide waveform codingin bandwidth-limited channels (i.e., where bandwidth expansion is notpossible). For example, Trellis-coded CI modulation may be used.Structured sequences add parity digits to data such that the paritydigits can be employed for detecting and/or correcting specific errorpatterns. Error-correcting codes (e.g., forward-error correction orerror detection codes) may be based on CI coding. CI coding may beapplied to block coding and convolutional coding. Polyphase CI codes maybe implemented as cyclic codes.

The multiplexing step 6805 controls a user's access to a fixedcommunication resource. Multiplexing provides the means to efficientlyallocate portions of the communication resource to a number of users.Basic multiplexing and multiple-access techniques include frequencydivision, time division, code division, space division, and polarizationdivision. Each of these techniques can be performed in a CI-based systemby appropriate selections and/or adjustments of CI carriers.

CIMA can be represented as a type of multiplexing based oninterferometry division. Although CIMA resembles code division multipleaccess because its phase spaces can be regarded as polyphase codes(particularly, time-domain CI codes), CIMA can be adapted to CDMA, TDMA,and frequency division multiple access.

The modulation step 6806 involves choosing a modulation type to achievea desirable balance between various objectives, such as maximizingthroughput, minimizing probability of error, optimizing bandwidthefficiency, improving SNR, and reducing system costs and complexity.Modulation may be coherent or non-coherent. Modulation may be analog ordigital. Modulation may include phase modulation, amplitude modulation,frequency modulation, or any of various hybrid modulation techniques.Modulation may include continuous-phase modulation.

Modulation is provided in a CI-based system by modulating one or more CIcarrier values. CI may be referred to as a form of multicarriermodulation. For example, phase modulation is provided to a CIsuperposition signal by phase-modulating the individual carriercomponents. Amplitude modulation is performed by adjusting one or moreCI carrier amplitudes. Frequency modulation may be performed by anycombination of selecting CI carrier frequencies and adjusting thecarrier values.

The spreading step 6807 may include redundantly modulating data symbolsover a plurality of carriers. Frequency-domain spreading may be providedvia conventional direct-sequence coding and/or CI coding. This type ofcoding may be generated by any combination of selecting and adjustingthe CI carriers. CI carriers may be selected to span discontinuousfrequency bands, avoid interference and/or jamming, and/or mitigate theeffects of multipath fading.

Multiple access 6808 may include any number of polling and accessalgorithms. For example, carrier sense or token ring multiple accesstechniques may be employed. Physical layer multiple access is preferablyemployed at the CI-carrier level. Framing can involve providing apredetermined number of symbols in a fixed time interval. In CI systems,framing can be performed by selecting a number of CI carriers that isrelated to the number of symbols in a frame. The frequency separationbetween carriers may be related to the inverse of the frame duration.Data symbols are positioned in the frame via carrier weighting, whichmay be adjusted at frame-duration intervals.

Headers, trailers, training sequences, payload segments, and othersymbol groupings (even discontinuous groupings) may be regarded assubframes and processed in the same way as frames are processed. In oneset of embodiments, subframes may be processed and then combinedtemporally. In another set of embodiments, each subframe may beprocessed as a subset of carriers. In yet another set of embodiments,each subframe is processed simultaneously as a calculation orapplication of weights to at least a subset of CI carriers. Thecalculations or weights are combined to generate an aggregatecarrier-weight set that generates a superposition signal indicative ofthe frame. Higher-than-physical-layer techniques are typically performedby systems that may provide control signals to adjust carrier weightingand/or selection to implement the physical-layer controls for multipleaccess.

The transmit step 6809 may preprocess the modulated signals to optimizethe signals for transmission in the channel 99. Basic components of atransmitter typically include a frequency up-conversion stage, a poweramplifier, and an output coupler (e.g., an antenna). The transmit step6809 may include selecting or adjusting transmitted signal frequenciesto mitigate interference, reduce the effects of channel distortion,provide power control, and/or conform to spectrum allocations. Thetransmit step 6809 may provide carrier weighting for beam forming orother spatial interferometry applications. The transmit step 6809 mayfilter or predistort the transmitted signals. The transmit step 6809 mayfurther include one or more adaptation steps (not shown) that providefor adjustment of transmission and/or transmit-signal characteristicsbased on feedback or blind adaptive processing.

The receive step 6819 couples transmitted signals out of the channel6819 and optionally converts the received signals into a form thatfacilitates IF and/or baseband processing. Basic components of areceiver include an input coupler for receiving signals from the channel99, a low-noise amplifier, and a down-converter stage that down convertsreceived signals to IF or baseband. The receive step 6819 may includeselecting or adjusting received signal frequencies to mitigateinterference, reduce the effects of channel distortion, provide channelselection, and/or optimize some performance measurement. Weights may beapplied to received signals for beam forming, spatial interferometry,and/or optimal combining. The receive step 6819 may include adaptiveprocessing and/or probing techniques that adjust one or more physicalparameters of the received signals. The receive step 6819 may generatecommands based on channel estimates to control transmissioncharacteristics of a local or remote transmitter.

The multiple-access step 6818 selects one or more signals by processingCI carriers. Alternatively, conventional demultiplexing techniques canbe used. A CI superposition signal has similar time-domaincharacteristics as a conventional single-carrier signal.

Frequency-division demultiplexing can be performed by selectingpredetermined CI carriers following a Fourier transform or otherfiltering operation. Code-division demultiplexing can be performed byfrequency-domain decoding. Demultiplexing in the spatial domain caninvolve providing weights to carriers from each of a plurality ofreceiver elements to separate desired signals from interfering signals.Similarly, spatial processing can be performed via frequency-diversityinterferometry.

Time-division demultiplexing can be performed by matched filtering,orthogonal frequency Fourier transforms, or equivalent signal-processingtechniques applied to CI carriers. An advantage of CI-based reception oftime-domain signals is that each symbol is processed over a timeinterval that is substantially longer than the apparent symbol (e.g.,pulse) duration. The symbols are also processed in parallel. Thesesignal-processing advantages enable the adaptation of conventionalparallel processing to CI systems. Low-speed parallel processing alsofacilitates the implementation of software-based applications (such aserror detection, error correction, authorization, verification, andother security-related applications) for high-speed communicationnetworks.

The despreading step 6817 can involve spread-spectrum decoding and/orcarrier selection and grouping. Decoding can take the form ofcode-division demultiplexing. Since CI carriers corresponding to aparticular channel or user can be distributed over one or more frequencybands, carrier selection follows a filtering operation that separates areceived CI signal into its carrier components.

The demodulation step 6816 may include coherent or non-coherentdetection. Detection may include sampled matched filtering, envelopedetection, differential detection, correlation, etc. These techniquescan be performed with respect to individual carriers or with respect toa superposition of the carriers. In some cases, an orthogonalsample-and-sum operation can provide filtering and demodulation.

The demultiplexing step 6815 can be provided to the CI carriers in acombining step. Channel decoding 6814, as well as other steps in thereceiver 6820 may include carrier selection, time interval selection(e.g., integration period), weight generation, carrier weighting, and/orcombining.

The decryption step 6813 provides any necessary physical-layer and/ordata-layer decryption. Physical layer decryption may includecarrier-frequency selection, spread-spectrum decoding, carrier-phasedecoding, time-base decoding (e.g., pulse-position decoding,time-hopping decoding, space-time decoding, etc.), signal de-masking,polarization decoding, and/or any other diversity parameter relateddecoding. Data-layer decoding may be performed via carrier processing.For example, a data decryption key may be translated into complexcarrier weights that are provided to CI carriers or signal valuesderived from the carriers. Alternatively, data decryption may beperformed following CI carrier processing.

The source-decode step 6812 and/or the formatting step 6811 reduces areceived waveform to a set of numerical values. This operation can beperformed with a linear filter coupled to a sampler. Similarly, amatched filter or correlator may be used. Signal detection provides acomparison of the value set to a threshold level or a constellation ofvalues.

FIG. 69B illustrates different embodiments of the formatting step 6811relative to the type of information being processed by the receiver6820. Signals processed by a waveform detector 6831 are output forformatting 6811. The formatting step 6811 passes digital information,performs decoding 6832 for textual information, and provides anadditional step of low-pass filtering 6833 for analog information. Theformatted information may be provided to an information sink (notshown).

A receiver may process a received signal by one or more detectionschemes, including matched filtering, optimal combining, and multi-userdetection. CI can be used in one or more of these detection schemes. Inone example, CI sampling provides a simplified form of matchedfiltering. Formatting 6811 may include source coding and decodingprocesses, such as block coding, synthesis/analysis coding,redundancy-reducing coding, etc. CI coding may be used in source codingand decoding processes.

CI Sampling

Principles of CI may be applied to many different types of signalprocessing. In one set of embodiments of the invention, sample valuesare collected and processed according to mathematical principles of CI.In one aspect of the invention, correlation and filtering (such asmatched filtering) may be performed without multiplication. In anotheraspect of the invention, various types of spectrum analysis andsynthesis may be performed to provide a substantial reduction orelimination of complex multiplications and/or additions. In anotheraspect of the invention, phase and/or amplitude adjustment is providedto the samples to compensate for interference, noise, and/or channeldistortion (such as multipath effects).

Applications of CI to sampling include processing received CI carriersignals and/or separating a received signal into a plurality oforthogonal CI signals. The process of decomposing a signal into one ormore orthogonal carrier components involves selecting an appropriatesampling interval (i.e., symbol duration T_(s)) relative to thecarrier-frequency separations. Similarly, various CI techniques forgenerating CI-based signals include selecting a symbol duration T_(s)corresponding to the carrier-frequency separation f_(s).

FIG. 70 shows three orthogonal waveforms 7001, 7002, and 7003 separatedin frequency by integer multiples of a separation frequency ƒ_(s). Insome cases, the waveforms 7001, 7002, and 7003 may be sub-carriermodulations. Similarly, the waveforms 7001, 7002, and 7003 may becharacterized by orthogonal circular (or elliptical) polarization spinfrequencies. Data symbols may be impressed onto each waveform within asymbol interval T_(s)=1/ƒ_(s). The symbol interval and/or adjacentintervals may include guard intervals and/or cyclic prefixes, which arewell known in the art.

In order to separate a data symbol modulated on a particular waveformfrom interference contributed by other waveforms, the set of waveformsis first sampled at a sampling frequency ƒ_(sample) that equals adesired waveform frequency ƒ_(n), or some harmonic or sub-harmonicthereof. The desired waveform's frequency ƒ_(n) can be expressed as:

ƒ_(n)=ƒ₀ +nƒ _(s)

where ƒ₀ is a base or carrier frequency and n is some integer. In thiscase, frequencies of the adjacent waveforms can be expressed as:

ƒ_(n±1)=ƒ₀+(n±1) ƒ_(s)

A number N of samples are represented in FIG. 70 by equally spaced timeintervals 7010.0 to 7010.N corresponding to an integer multiple of adesired waveform's period. In this example, the sample intervals 7010.0to 7010.N intersect the peaks of a desired waveform. However, the sampleintervals 7010.0 to 7010.N intersect the other waveforms at variousparts of their cycles. An important aspect of the invention involvesselecting the time interval (or symbol duration T_(s)) over whichsamples are combined. The symbol duration T_(s) defines the frequencyspacing ƒ_(s)=1/T_(s) of orthogonal waveforms. When N samples collectedover a period T_(s) are combined, a desired signal can be separated frominterfering signals modulated on orthogonal waveforms.

One type of sampling that may be performed with CI sampling methods (asillustrated in FIG. 70) is known as under sampling, which is describedby the well-known Passband Sampling Theorem. An improvement provided byCI sampling consists of combining samples obtained during one or moresymbol intervals T_(s) to separate at least one desired symbol fromsymbols impressed on other waveforms.

The following explanation illustrates a simple case in which symbols aredemodulated from one particular sub-carrier frequency in the presence ofother sub-carrier frequencies. In this case, ƒ_(sample)=ƒ_(n). FIG. 71Ais a normalized complex-plane representation of how the sampling rateƒ_(sample)=ƒ_(n) relates to the desired waveform's frequency ƒ_(n).Since ƒ_(sample)=ƒ_(n), the samples always occur on the same part of thecomplex plane, such as on the real axis at 1. The number of samplesN_(s) per symbol interval T_(s) is expressed by:

N _(s)=ƒ_(sample) T _(s)=(ƒ₀ +nƒ _(s))/ƒ_(s)

The number of samples per waveform period (1/ƒ_(n)) is 1.

FIG. 71B and FIG. 71C are normalized complex-plane representations ofhow the sampling rate ƒ_(sample) relates to frequencies of the adjacentwaveforms. The number of samples per period of the adjacent waveformhaving frequency ƒ_(n−1) can be expressed as:

$N_{n - 1} = {\frac{f_{n - 1}}{f_{sample}} = {1 - \frac{f_{s}}{\left( {f_{o} + {nf}_{s}} \right)}}}$

FIG. 71B shows each subsequent sampled value shifted by:

$\varphi_{n - 1} = {{- \frac{f_{s}}{\left( {f_{o} + {nf}_{s}} \right)}}2\; \pi \mspace{14mu} {{radians}.}}$

Since there are N_(s)=(ƒ₀+nƒ_(s))/ƒ_(s) samples per symbol intervalT_(s), the vector samples fill one full rotation of the normalizedcomplex plane, as shown in FIG. 72. Thus, the vector sum of the samplesis zero.

The number of samples per period of the adjacent waveform havingfrequency f_(n+1) can be expressed as:

$N_{n + 1} = {{\frac{f_{n + 1}}{f_{sample}}1} + \frac{f_{s}}{\left( {f_{o} + {nf}_{s}} \right)}}$

FIG. 71C shows that in the complex plane, the sampled values shift by anamount:

${\varphi_{n + 1} = {\frac{f_{s}}{\left( {f_{o} + {nf}_{s}} \right)}2\pi \mspace{14mu} {{radians}.}}}\;$

The N_(s) samples collected throughout the symbol interval T_(s) alsoprocess through one full rotation of the complex plane, but in theopposite direction. The vector sum of these samples (also represented byFIG. 72) is zero.

The number of samples per period of any adjacent waveform having afrequency ƒ_(n±n′) can be expressed as:

${N_{n\underset{\_}{+}n^{\prime}}\frac{f_{n\underset{\_}{+}n^{\prime}}}{f_{sample}}} = {1\underset{\_}{+}\frac{n^{\prime}f_{s}}{\left( {f_{o} + {nf}_{s}} \right)}}$

In the complex plane, the sampled values shift by an amount:

$\varphi_{n\underset{\_}{+}n^{\prime}} = {{\underset{\_}{+}\frac{n^{\prime}f_{s}}{\left( {f_{o} + {nf}_{s}} \right)}}2\pi \mspace{14mu} {{radians}.}}$

N_(s) samples collected throughout the symbol interval T_(s) processthrough n′ rotations of the complex plane and cancel unless ƒ_(n±n′) isan integer multiple of ƒ_(n). The case in which ƒ_(n±n′)=mƒ_(n) (where mis some integer) can be avoided by providing appropriate frequencyadjusting to either or both signal frequencies and sample frequencies.Thus, the vector sum of the samples is zero.

In one aspect of CI sampling, orthogonal frequency channels are easilyseparated using only sampling and adding processes. One application ofthis invention includes frequency-division demultiplexing. Coherent CIsampling may be performed by receivers designed for multicarriertransmission protocols, including CI, OFDM, and MC-CDMA.

In-phase and quadrature-phase samples may be generated by sampling at aquarter-wave offset to the sampling period of a first set of samples.FIG. 73 illustrates two sets of samples having the same desiredfrequency and a π/2 phase offset between them. Both in-phase andquadrature-phase samples of a particular frequency produce the samevector sum of zero for orthogonal frequencies when samples collectedover a corresponding time interval T_(s) are combined.

Any appropriate sampling method may be used to generate in-phase andquadrature-phase samples for the purpose of this invention. In oneembodiment, a delay offset is provided to one of two identical timingsignals used to trigger a sample-and-hold circuit. In anotherembodiment, a high-rate timing signal is used to trigger asample-and-hold circuit and then undesired samples are discarded beforecombining. In another set of embodiments, an input signal may be undersampled and the in-phase and quadrature-phase samples may have a π/2phase offset relative to at least one desired frequency components. Acombining process may include adding and/or subtracting samples. Acombining process may optionally include weighting.

FIG. 74A illustrates the combined values of 110 CI samples for each of400 frequencies in intervals of one cycle per symbol period T_(s). Sincethe sampling rate is 110 samples per symbol period T_(s), non-zero sumsoccur at 110 cycles-per-symbol intervals. All other integercycles-per-symbol frequencies correspond to integer-valued rotationsaround the complex plane that sum to zero.

FIG. 74B illustrates the combined values of 110 CI samples for each of800 frequencies spaced at 0.05 cycles-per-period intervals and centeredat 110 cycles per symbol period. The sums corresponding to non-integercycles-per-symbol frequencies have non-zero values.

FIG. 74C illustrates a plot of sums of samples collected at a particularsample frequency for different sampled signal frequencies. The sums arefrom a plurality of samples collected over a given symbol intervalT_(s). The signal frequencies are centered at 110 cycles per symbol andextend 8 cycles per symbol on both sides of the center frequency.

A center peak 7400 may correspond to a signal frequency that is aharmonic or sub-harmonic of the sample frequency. Zero values, such asillustrated by zero-crossing positions 7401 to 7407, occur at integercycles-per-symbol frequencies relative to the center frequency. Thezero-crossing positions, such as positions 7401 to 7407, indicatefrequencies that are orthogonal to the center frequency. When generatingorthogonal sub-carrier frequencies, it is desirable to position thefrequencies at zero crossings, such as illustrated in FIG. 74C. Thezero-crossing positions depend on the symbol interval T_(s) over whichthe samples are combined, and thus, can optionally be adjusted withrespect to adjustments to the symbol interval T_(s).

FIG. 74C also illustrates contributions of various frequencies to thecombined samples. Signals modulated onto frequencies that are notcentered at zero-crossing positions contribute non-zero values to thecombined samples. In some spectrum-analysis applications, samples thatare combined at one or more sample frequencies may be weighted and/orcombined with samples collected at one or more different frequencies.Zero-crossing positions, as well as side-lobe height and main-lobe widthcan be selected and/or adjusted by providing appropriate complex weightsto the samples.

FIG. 75 illustrates sums of samples collected at a particular samplefrequency f_(n) for different sampled signal frequencies. A peak 7500occurs when the sampled signal frequency equals the sample frequencyƒ_(n). The sum at sample frequency ƒ_(n) is represented by FIG. 76A,which illustrates each sample as a normalized vector mapped in a complexplane. Because the sample and sampled signal frequencies are equal, eachsample coincides with the same location of each period of the sampledsignal. In this case, all the vectors map onto each other in thepositive real axis (i.e., +1), resulting in totally constructivecombining.

A first zero crossing 7501 is illustrated in FIG. 75. The sampled signalfrequency equals the sample frequency ƒ_(n) plus one cycle-per-symbolduration. Thus, the sampled signal frequency ƒ_(n+1) is orthogonal tothe sample frequency ƒ_(n). The sample sum at ƒ_(n+1) is represented bya complex-plane mapping illustrated in FIG. 76B. Because the samplefrequency ƒ_(n) and the sampled signal frequency ƒ_(n+1) differ, thesample values intersect different parts of the sampled signal. Since thefrequencies ƒ_(n) and ƒ_(n+1) are orthogonal and differ by one cycle persymbol duration, the sample values map to uniformly spaced vectors overa unit circle. This results in a vector sum of zero. A first side-lobepeak 7502 illustrated in FIG. 75 corresponds to a sampled signalfrequency that equals the sample frequency ƒ_(n) plus one and one halfcycles per symbol. The sampled signal frequency ƒ_(n+1.5) is notorthogonal to the sample frequency ƒ_(n). The vectors representing thesample values fill one and one half rotations throughout the complexplane. The vectors in the one-half plane shown in FIG. 76C combinesubstantially constructively to produce the side-lobe peak 7502. Sinceapproximately two-thirds of the vectors are distributed uniformlythroughout one rotation (and thus, cancel), the side-lobe peak 7502 issubstantially lower than the main-lobe peak 7500.

A second zero crossing 7503 is represented by a vector mappingillustrated in FIG. 76D. The sampled signal frequency equals the samplefrequency ƒ_(n) plus two cycles per symbol. Thus, the frequencies ƒ_(n)and ƒ_(n+2) are orthogonal and the sample values map to vectorsuniformly distributed around two full unit circles in the normalizedcomplex plane. In this case, the vectors shown in FIG. 76D overlap othervectors.

A second side-lobe peak 7504 corresponds to a sampled signal frequencythat equals the sample frequency ƒ_(n) plus two and one half cycles persymbol. Four fifths of the corresponding vectors are mapped over tworotations in a normalized complex plane and thus, cancel. The remainingvectors are distributed over a half rotation in the complex plane, asillustrated by FIG. 76E. The vector sum produces the peak 7504, which islower than the first side-lobe peal 7502.

Additional zero crossings and side-lobe peaks, as well as other sums,may be represented by the vector-mapping techniques previously describedherein. These techniques may be used to describe, as well as construct,signals having similar characteristics. For example, CI signals, arraybeam patterns, diffraction patterns, and other types of interferencepatterns may be described by vector maps and/or constructed usingprocesses that correspond to vector mapping.

FIG. 77A is a functional diagram that illustrates one aspect of coherentCI sampling as it applies to several apparatus and method embodiments ofthe present invention. The general nature of the functional diagram isthe basis of a large number of embodiments of this aspect of theinvention.

An input signal Σs_(n)(f,t) includes multiple signal components havingorthogonal frequencies. Other diversity parameters of the components mayalso be orthogonal. In some cases, orthogonal frequencies may refer topolarization spin frequencies, subcarrier modulation frequencies, arraypattern scan frequencies, direct sequence code repetition rates, and/orfrequencies that characterize cyclic properties of any otherdiversity-parameter values.

The input signal is processed in a sampler 7701, which is a device orprocess that samples an input signal with respect to one or morediversity parameters. In one set of embodiments, the sampler 7701 usesat least one reference timer signal τ to produce samples in the timedomain. The reference timer signal(s) τ may be generated internally orexternally with respect to the sampler 7701. The sampler 7701 maygenerate one or more sets of samples with respect to one or morediversity parameter values (e.g., timing signals, carrier frequencies,etc.).

In one embodiment, each set of samples corresponds to a differentsampling rate. In another embodiment, a first set of samples iscollected with respect to one sampling rate ƒ_(sample) and additionalsample sets are generated as subsets of the first set. Thus, the subsetfrequencies ƒ_(sample)(n) are less than the sampling rate ƒ_(sample). Inat least one embodiment, the sampler 7701 may sample the input signal ata sampling frequency f_(sample) corresponding to one or more frequenciesof the input signal. In at least one embodiment, the sampler 7701 mayunder sample and/or over sample one or more signal components of theinput signal.

Samples from the sampler 7701 are input to a combiner 7702. The combiner7702 is adapted to sum or otherwise combine two or more samples. Thecombiner 7702 combines at least one set of samples that corresponds toat least one symbol interval T_(s). The symbol interval T_(s) isprovided with respect to the relationship T_(s)=1/ƒ_(s) such that atleast one data symbol on at least one carrier can be separated frominterfering data symbols on one or more carriers that are orthogonal tothe desired carrier(s). Thus, the process of summing the selectedsamples over a predetermined symbol interval T_(s) provides forfiltering of orthogonal carriers that are not aliased by the samplingprocess. In some applications, sampling and summing may be performed todecompose a single-carrier signal into a plurality of predetermined CIcarriers. In other applications, a received multicarrier signal may bedecomposed into a different set of carrier signals or carrier-signalvalues.

The sampler 7701 and/or combiner 7702 may include a storage device (notshown) to store samples before combining them. The combiner 7702 mayseparately combine subsets of samples and/or it may combine all of thesamples together. An output signal s(ƒ_(n),t) represents the combinedsamples output by the combiner 7702. In one embodiment, the value of theoutput signal corresponds to at least one frequency components of theinput signal and the sampling frequency ƒ_(sample). The samplingfrequency ƒ_(sample) may have the same value as ƒ_(n), a harmonic ofƒ_(n), or a sub-harmonic of ƒ_(n) in order to extract the value(s) ofthe input signal associated with ƒ_(n). In particular, this combinationof sampling and combining can be used to demodulate data symbolsimpressed on one or more frequencies ƒ_(n) without requiring complexdigital processing.

The sampler 7701 and/or the combiner 7702 may include a weighting device(not shown) capable of applying weights to the samples and/or sums ofthe samples. The weights may be complex valued. In some embodiments,weight values may be provided by shifting or otherwise adjusting theorder of the samples. These weights may be used to compensate forchannel effects and/or signal coding. An optimal-combining process maycontrol the weights to enhance reception of desired signals in thepresence of noise and/or interference.

The combiner 7702 may preferentially weight and/or combine certaincombinations of samples with respect to the waveform and/or coding ofthe received signal. Weights may be applied to the received samples tocompensate for any mismatch between the sampling frequency ƒ_(sample)and the frequency ƒ_(n) of at least one desired signal component. If adesired frequency component is over sampled, some of the samples may bedisregarded to enhance reception (e.g., improve SNR, SNIR, BER,probability of error, etc.) of the desired signal.

Although FIG. 77A illustrates one type of CI sampling that is useful forseparating data symbols impressed on multiple orthogonal frequencychannels, variations to this method and apparatus may be employed.Furthermore, CI sampling may be used to separate data symbols modulatedonto other orthogonal diversity parameters, such as polarization, time,spreading code, phase space, subspace, angle of arrival, etc.

FIG. 77B illustrates a functional diagram for an apparatus and method ofthe present invention. An input signal Σs_(n)(f,t) may include multiplesignal components characterized by frequencies that are orthogonal.Alternatively, the input signal Σs_(n)(f,t) may include one or moresingle-carrier signals. The input signal Σs_(n)(f,t) is processed by asampler 7701 that includes in-phase and quadrature-phase sampling units77011 and 7701Q, respectively. The sampler 7701 receives at least onepair of timing signals τ(0) and τ(π/2) having a relative phase offset ofπ/2. Each pair of timing signals τ(0) and τ(π/2) may correspond to adifferent CI carrier frequency ƒ_(n). Thus, a timer (not shown) mayperform appropriate frequency-dependent processing to producequarter-wave phase offsets π/2. Each sampling unit 77011 and 7701Qgenerates a plurality of samples at one or more sample frequenciesƒ_(sample).

The samples are combined in a combiner 7702. In this case, the combiner7702 includes in-phase and quadrature-phase combining units 77021 and7702Q. Sample sets corresponding to one or more symbol intervals T_(s)are combined. In one embodiment, the samples are combined separatelywith respect to at least one predetermined sample frequency over atleast one predetermined symbol interval T_(s). In another embodiment,the samples are combined without respective to any periodic samplingfrequency. Samples may be selected at random, pseudo-random, orotherwise non-periodic intervals. Combining may be coherent ornon-coherent.

The combiner 7702 outputs in-phase and quadrature signals s_(l)(f,t) ands_(Q)(ƒ_(n), t) that may optionally be processed in at least one signalprocessor 7703. The in-phase and quadrature-phase signals s₁(ƒ_(n),t)and s_(Q)(ƒ_(n),t) correspond to one or more frequency components ƒ_(n)and symbol values occurring in time interval T_(s). Optionally, thesesignals may be combined coherently or non-coherently in the processor7703. In one embodiment, the processor 7703 generates an output signals(φ,a, ƒ_(n), t) having a particular phase φ and amplitude Acorresponding to a CI carrier frequency ƒ_(n) and a symbol intervalT_(s). The phase φ and/or amplitude A may be used to identify atransmitted symbol. Phases φ may be represented by time offsets.Alternatively, or additionally, phases φ and amplitudes A may beprocessed to characterize the propagation channel and generate receiverand/or transmitter channel-compensation weights. In other embodiments,the processor 7703 may produce a modulated signal that may optionally bedemodulated.

Various method and apparatus embodiments of the invention are summarizedby the following functional descriptions:

Type 1: Sampling Orthogonal Carrier Frequencies.

An input signal including a set of orthogonal carriers is sampled at oneor more sample rates ƒ_(sample) that include at least one CI carrierfrequency ƒ_(n) and/or some subharmonic thereof.

The samples are summed (or otherwise combined) over at least one symbolinterval T_(s).

In the case where multiple sample rates ƒ_(sample) are employed, samplescorresponding to each sample rate ƒ_(sample) may be combined separately.Sampling and/or summing may include accumulating or storing the samples.If samples are collected at multiple frequencies ƒ_(sample), the samplesmay be separated with respect to sample frequency ƒ_(sample) beforebeing stored and/or combined. In one set of embodiments, samplescorresponding to a particular sampling frequency ƒ_(sample) arepreferably summed separately from samples corresponding to other samplefrequencies. Samples collected at multiple frequencies ƒ_(sample) may besorted, arranged, rearranged, shifted, or stored in a predeterminedorder.

Sampled values may be stored in a predetermined order and the storedvalues may be further sampled, selected, or rearranged prior tocombining. Any type of signal having orthogonal carrier (or sub-carrier)frequencies may be CI sampled, including OFDM, MC-CDMA, CIMA, CI,circular polarized, Discreet Multitone, FDM, WDM, ultra-dense WDM, MCDS-CDMA, and multi-tone signals. The orthogonal carrier frequencies maybe up converted or down converted in frequency prior to sampling.Combined samples may be multiplied by a complex weight. Similarly,samples may be weighted prior to combining.

Type 2A: Sampling a CI Signal.

The phase of each sample frequency ƒ_(sample) is set to at least oneparticular phase space.

Samples collected at each sample frequency ƒ_(sample) are summed over atleast one symbol interval T_(s).

One or more of the sums are multiplied by a complex weight (optional).

Sums corresponding to a particular phase space are summed.

A decision process determines symbol value(s) associated with each phasespace.

Type 2B: Sampling a CI Signal.

The phase of each sample frequency ƒ_(sample) is set to at least oneparticular phase space.

Samples at all sampling frequencies ƒ_(sample) for the particular phasespace are summed over at least one symbol interval T_(s).

A decision process is used to determine what symbol(s) was modulatedonto each phase space.

Type 2C: Sampling a CI Signal.

The phase of each sample frequency ƒ_(sample) is set to a particularphase space or set of phase spaces. For example, in-phase (I) andquadrature-phase (Q) samples may be collected.

Samples collected at each sampling frequency ƒ_(sample) are summed overat least one symbol interval T_(s). I and Q samples may be summedseparately.

One or more of the sums are multiplied by a complex weight (optional).

Magnitude and/or phase for each frequency ƒ_(sample) is determined fromthe corresponding sum(s).

A decision process determines on or more symbol values associated witheach frequency ƒ_(sample).

A decision process may determine the value associated with each phasespace (optional).

Multiple phase spaces may be evaluated in parallel. The samplefrequencies f_(sample) may include one or more subharmonics of theorthogonal carrier frequencies ƒ_(n). The sample frequencies ƒ_(sample)may include subharmonics of one or more of the orthogonal carrierfrequencies ƒ_(n). Each sample frequency ƒ_(sample) may includeharmonics of one or more of the orthogonal carrier frequencies ƒ_(n).The process of summing the samples may be preceded by selecting ordiscarding some of the samples.

Type 3: Deriving Low-Rate Samples from a Set of Samples Collected at aHigher Rate.

A received waveform is sampled at some high sampling rate ƒ_(h).

Samples are selected with respect to at least one desired sample phaseand at least one desired sample frequency ƒ₁, where ƒ₁<ƒ_(h). Samplescorresponding to a desired sampling rate (or some harmonic orsubharmonic thereof) are selected. Selective decimation may beperformed.

The selected samples are summed.

A decision process is optionally provided to determine what symbol(s)was modulated onto at least one frequency, at least one phase space, orany combination thereof.

Type 3 CI sampling may result in slightly poorer precision (due, atleast in part, to quantization error) compared to other types of CIsampling. However, the reduced complexity of using a single samplingfrequency ƒ_(h) can be weighed against the slight performancedegradation (which appears to be negligible for relatively high samplerates f_(h)). Sample weights may depend on proximity of actual samples(corresponding to ƒ_(h)) to desired samples (corresponding to ƒ₁).

Groups of samples may be selected. For example, samples straddling adesired sample point may be combined. Samples may be discarded if theydo not fall within a predetermined proximity to desired sample points.For example, only sample points that are within some time period of thedesired samples may be summed. Samples may be selected to minimizeprobability of error, SNR, BER, signal-to-interference, SNIR, oroptimize some other performance measurement that characterizes thequality of the estimated data symbols. The received signal may be upconverted or down converted prior to sampling. Sampling may beintegrated into a down-conversion process, such as passband sampling. Inany of the CI sampling cases, a received signal may be filtered prior toor following sampling.

FIG. 78A shows part of a coded CI waveform 7800 that may be processedusing a CI algorithm, such as an algorithm based on the Type 3 CIsampling method. The waveform 7800 shown is distorted relative to amultipath channel distortion model. The signal is constructed from 10carriers having a frequency spacing of ƒ_(s)=100 kHz. The algorithmsamples the received CI waveform at 10 MHz to generate 100 sample pointsacross the 10-μsec symbol interval T_(s). Typically, more than 100sample points would be generated across a symbol interval T_(s). In thiscase, there are 10 phase spaces and thus, 10 symbols occurring withinthe symbol interval. Alternatively, quasi-orthogonal pulse shaping maybe used to provide up to 20 symbols.

The algorithm collects samples from the sampled waveform correspondingto the 10 phase spaces and the 10 frequencies associated with each phasespace. The most appropriate of the 100 sample points is selected foreach sample of each phase-space/frequency combination. The selection ofsample sets to be summed may be performed only once. The combinationsmay be used for subsequent sets of samples as long as the sample rateand the desired phase-space/frequency combinations are not changed.Samples corresponding to each phase space are summed to provide a signalrepresenting one of the transmitted symbols. As the granularity of thesampling (i.e., the sample frequency ƒ_(h)) is increased, greaterprecision is achieved with respect to measuring received data symbols.FIG. 78B shows a table that illustrates 10 transmitted data symbols andthe corresponding non-normalized received signal for each of the 10phase spaces.

Individual sample values may be added or subtracted depending on thepart of a desired waveform cycle with which they correspond. Thisadaptation is implied by the term combining, as used herein. Sampleshaving low values typically have relatively low SNRs. Accordingly, someapplications may remove samples having values below a predeterminedthreshold. In some combining embodiments, sample values may be weightedwith respect to a multi-level step function. The step function typicallyhas the same frequency (and possibly phase) of at least one desiredcarrier signal. The step-function levels may approximate (either closelyor roughly) the desired waveform's amplitude. Appropriate weightingand/or selection processes are also implied by the function of combiningfor both channel compensation and step-function processes.

Although impulse sampling is illustrated herein for simplicity, variousforms of sampling may be provided, such as sample and hold. Othersampling techniques may be employed within the scope of the invention.Natural sampling (such as described in B. Sklar, Digital CommunicationsFundamentals and Applications, Prentice-Hall, Inc., New Jersey, 1988,which is incorporated by reference) involves multiplying a band-limitedwaveform by a pulse train or switching waveform. Sample widths may beprovided to collect substantial amounts of the received waveform energy.In some applications, sample widths may be on the order of half thewavelength of a desired waveform in a multicarrier signal. In otherapplications, sample widths may be approximately half the wavelength ofa predetermined CI waveform component into which a received signal isprocessed. In some applications, sub-harmonic (i.e., passband) samplingmay be performed to provide a combined down-conversion/filteringoperation. Furthermore, the sampling processes disclosed herein may beintegrated into Fourier or similar transform operations.

In one set of embodiments, signals are filtered with respect to at leastone orthonormal basis by inputting a multicarrier signal (defined by theat least one orthonormal basis) into a processor (not shown) adapted tocorrelate the input signal with a sum of values pertaining to the atleast one orthonormal basis. This process is distinguishable fromcombining correlations of the input signal with various values of theorthonormal basis. Various types of orthonormal bases may be used, suchas wavelet, Fourier, Hadamard-Walsh, Laplace, and Lorentz, as well asother orthonormal bases.

CI OFFT

The Fourier transform of a time-domain signal into its frequency-domaincomponents is expressed by:

X(f) = ∫_(−∞)^(∞)x(t)^( 2π fl)δ t. 

The corresponding discreet Fourier transform (DFT) equation is expressedby:

${X\left( f_{n} \right)} = {\sum\limits_{k = 0}^{K - 1}{x_{k}^{{- }\; 2\; \pi \; f_{n}{kl}_{a}}}}$

where K is the number of time-domain samples collected over a period ofT_(s)=Kt₀. Several simplifications can be made when orthogonalfrequencies are processed. The orthogonal frequencies ƒ_(n) areexpressed by:

ƒ_(n)=ƒ₀ +nƒ _(s)

and the sampling period is T_(s)=1/ƒ_(s).

When orthogonal frequencies are sampled and processed with a DFT, avalue in a particular frequency bin ƒ_(n) corresponds to time-domainsamples x_(k) multiplied by complex values e^(i2πƒ) ^(n) ^(ky) ⁰ . Sincemultiplication with a complex value is computationally intensivecompared to most signal-processing operations, it is desirable toreplace complex multiplications with simpler operations, such as addingand shifting. This is accomplished by replacing the complex valuee^(i2πƒ) ^(n) ^(kt) ⁰ (or any sinusoid representing a component of thecomplex value) with at least one periodic step function Γ(t, ƒf_(n), φ)having frequency ƒ_(n). For example, a periodic two-level step functionhaving at least one predetermined φ is expressed by:

${\Gamma \left( {t,f_{n},\varphi} \right)} = \left\{ \begin{matrix}{{- 1}\left( {{\cos \left( {{2\pi \; f_{n}t} + \varphi} \right)} < 0} \right)} \\{{+ 1}\left( {{\cos \left( {{2\pi \; f_{n}t} + \varphi} \right)} > 0} \right)}\end{matrix} \right.$

Other types of step functions may be used. For example, step-functionvalues do not need to be constrained to values of ±1. Step functionshaving more than two levels may be employed. Step functions may havemultiple phases φ. For example, in-phase and quadrature-phase stepfunctions may be employed.

The step function Γ(t, ƒ_(n), φ) can be expressed as a sum of harmonicsinusoids. For example:

${{\Gamma \left( {t,f_{n},\varphi} \right)} = {\sum\limits_{{n = 1},3,5,...}{\frac{\sin \left( {{2\pi \; f_{n}t} + \varphi_{n}} \right)}{n}.}}}\;$

FIG. 79A illustrates two periods of a step function 7901 constructedfrom a superposition of 100 odd-harmonic sinusoids generated withrespect to the step function Γ(t, ƒ_(n), φ). FIG. 79B illustrates aportion of a Fourier transform 7910 of the step function 7901. TheFourier transform 7910 shows 13 of the 100 component frequencies andtheir relative magnitudes on a logarithmic scale.

The step functions Γ(t, ƒ_(n), φ) are used in place of the periodiccomplex values e^(i2πƒ) ^(n) ^(kt) ₀ to simplify the DFT of a signal.This improvement is suggested by the DFT equation, which shows that thecomplex multipliers e^(i2πƒ) ^(n) ^(kt) ⁰ corresponding to frequency binƒ_(n) are periodic with respect to ƒ_(n). In one set of preferredembodiments, the sampled signal is band-limited such that only the ƒ_(n)frequency component of the step function Γ(t, ƒ_(n), φ) contributes tovalues of X(ƒ_(n)) in the orthogonal-frequency Fourier transform (OFFT)equation shown as follows:

${X\left( f_{n} \right)} = {\sum\limits_{k = 0}^{K - 1}{x_{k}{\Gamma \left( {t,f_{n},\varphi} \right)}}}$

The OFFT equation is similar to the DFT equation in its ability toquantify values in particular frequency bins. The OFFT is simpler thanother Fourier transform techniques because it replaces the complexvalues e^(i2πƒ) ^(n) ^(kt) ⁰ with step-function values, such as ±1,which can be implemented in an adding process. Thus, the OFFT replacescomplex multiplies with additions.

In the orthogonal-frequency case, the continuous form of the OFFT is theCI Orthogonal-Frequency Fourier Integral, or CIOFFI:

X(f_(n)) = ∫₀^(1/f_(s))cos (2π f_(n^(′))t + φ_(n^(′)))Γ(t, f_(n), φ)

where the cosine term represents at least one of the received carriershaving frequency ƒ_(n′). Assuming equality between all phase φ_(n′) andφ values, the continuous-form OFFT can be expanded as:

${X\left( f_{n} \right)} = {\frac{1}{2\pi \; f_{n^{\prime}}}\left\lbrack {\sin \; 2\pi \; f_{n^{\prime}}t\left. _{0}^{{1/4}f_{n}}{{- \sin}\; 2\; \pi \; f_{n^{\prime}}t\; {_{{1/4}f_{n}}^{{3/4}f_{n}}{{+ \ldots} + {\sin \; 2\pi \; f_{n^{\prime}}t}}}_{{1/4_{f_{n}}} + {2n} - {1/2_{f_{n}}}}^{0}} \right\rbrack} \right.}$

and simplified to:

${X\left( f_{n} \right)} = {\frac{1}{2\pi \; f_{n^{\prime}}}{\sum\limits_{k = 0}^{K - 1}{\left( {- 1} \right)^{k}\sin \frac{2\pi \; n^{\prime}y}{n}_{{{- 1}/4} + {k/2}}^{{1/4} + {k/2}}}}}$

where y is a dimensionless variable. Further simplification yields:

${X\left( f_{n} \right)} = {\frac{1}{\pi \; f_{n^{\prime}}}\sin \; \frac{\pi \; n^{\prime}}{2n}{\sum\limits_{k = 0}^{K - 1}{\left( {- 1} \right)^{k}{\cos \left( {\frac{\pi \; n^{\prime}k}{n} + \varphi_{m}} \right)}}}}$

The phase term φ_(m) indicates the possibility of a phase-modulatedinformation signal or a phase-space channel.

When the OFFT sample frequency ƒ_(n) equals the received carrierfrequency ƒ_(n′) (e.g., n=n′), the OFFT equation reduces to:

${X_{n = n^{\prime}}\left( f_{n} \right)} = {\frac{1}{\pi \; f_{n}}{\sum\limits_{k = 0}^{K - 1}{\left( {- 1} \right)^{k}{\cos \left( {{\pi \; k} + \varphi_{m}} \right)}}}}$

For each value of k, a π rotation of the vector (represented by thecosine term) is flipped by the −1 term. Thus, each k^(th) vector mapsonto a vector direction defined by the phase term φ_(m). Consequently,the terms of the OFFT that correspond to n=n′ combine constructively.

When the OFFT sample frequency ƒ_(n) does not equal the received carrierfrequency ƒ_(n′) (e.g., n≠n′), the OFFT equation is written as:

${X_{n \neq n^{\prime}}\left( f_{n} \right)} = {\frac{1}{\pi \; f_{n}}\sin \frac{\; {\pi \; n^{\prime}}}{2n}{\sum\limits_{k = 0}^{K - 1}{\left( {- 1} \right)^{k}{\cos \left( {\frac{\pi \; n^{\prime}\; k}{n} + \varphi_{m}} \right)}}}}$

For simplicity, it may be assumed that the number of samples K collectedis approximately some integer multiple of the sampled signal's cyclesper symbol interval. The approximation works well for large numbers ofsamples. Similarly, K can simply be set to some integer multiple of thesampling frequency ƒ_(n). Each value of X_(n≠n′)(ƒ_(n)) is aconstant-valued vector having an incremental angular offset of πn/n′.After an integer number of full rotations, the sum of the K vectors issubstantially zero. Thus, the terms of the OFFT that correspond to n≠n′combine destructively.

For ƒ₀=0, and n≠n′, constructive combining occurs under the followingconditions:

n=(2m+1)n′m=1,2,3, . . . .

The ranges of sampling and carrier frequencies can be expressed by astart frequency ƒ_(i) and an end frequency ƒ_(f′).

ƒ_(i)=ƒ₀+0ƒ_(s) =n ₀ƒ_(s)

ƒ_(ƒ)=ƒ₀+(n−1) ƒ_(s)=(n ₀ +n−1) ƒ_(s)

where the value of n₀ may be integer or fractional. This sets boundaryconditions on n and n₀ according to the following equation:

n<2n₀

Alternatively, the boundary conditions may be exploited in such a way asto perform Fourier transform operations via under sampling.

FIG. 80A is a frequency-domain representation that indicates a samplingfrequency 8000, which is a frequency component of a step function. Inthis case, the frequency component 8000 is a start frequency ƒ_(i) thatis orthogonal to a plurality of received frequency components 8001 to8006. Frequency component 8006 is designated as an end frequency ƒ_(f).If a received frequency component 8010 is a harmonic or subharmonic of astep-function component (such as frequency 8000), an OFFT or CI-samplingprocess that incorporates frequency 8000 is non-zero. Thus, OFFT and CIsampling may utilize harmonic and/or sub-harmonic frequencies relativeto at least one frequency component of a sampled signal.

In one embodiment of the invention, it is preferable to provide for bandlimiting of a received signal such that only one frequency component ofthe applied step function has a non-zero OFFT or CI-sampling result. Astep-function component and a received signal component may be relatedas harmonics or subharmonics. In another embodiment of the invention,the step function is adapted (e.g., filtered) to a given signal'sfrequency band.

FIG. 80B illustrates a frequency distribution of an alternate embodimentof an OFFT. Data symbols are redundantly modulated onto a plurality ofuniformly spaced carrier frequencies, such as frequencies 8000, 8010,and 8020. CI sampling or an OFFT are provided with respect to one ormore step-function frequencies that equal one or more of the frequencies8000, 8010, and 8020. Alternatively, the step-function frequenciesinclude one or more harmonics and/or subharmonics of the frequencies8000, 8010, and 8020. One or more additional step functions may beemployed in an OFFT or CI-sampling process corresponding to another setof frequencies (such as frequencies 8001, 8011, and 8021) that areorthogonal to the first set of frequencies 8000, 8010, and 8020.

FIG. 81 shows three sinusoidal waves 8101, 8102, and 8103 havinguniformly spaced frequencies ƒ₁, ƒ₂, and ƒ₃, and a step function 8111having a frequency equal to the frequency ƒ₁ of wave 8101. The value ofa frequency bin from a discreet Fourier Transform is represented by:

$y_{p} = {\sum\limits_{k = 0}^{K - 1}{x_{k}^{{- }\; 2\; \pi \; {{kp}/K}}}}$

In an OFDM system that employs BPSK modulation, the frequency-bin valuesare ±1. Similarly, other modulation schemes may be processed. A simplerway to determine these values is to replace the exponential term in theabove function with a step function. This eliminates the need forcomplex multiplications. The value of a frequency bin from the improvedFourier Transform is:

$y_{p} = {\sum\limits_{k = 0}^{K - 1}{x_{k}{\Gamma \left\lbrack {\tau_{n} = {1/f_{n}}} \right\rbrack}}}$

where the values of the step function are Γ[τ_(n)=1/ƒ_(n)]=±1. Thestep-function values vary with respect to the cycles of an n^(th)frequency, ƒ_(n).

In FIG. 81, the step function 8111 is set in phase with the wave 8101having frequency ƒ₁. In one embodiment of the invention, a valuecorresponding to frequency bin f₁ is obtained by adding and/orsubtracting the sampled waveforms in a manner indicated by the stepfunction 8111. The contributions to frequency bin ƒ₁ due to each of thethree frequencies ƒ₁, ƒ₂, and ƒ₃ are exemplified by sums of one thousandsample values shown as follows:

ƒ₁=637.5046

ƒ₂=−0.9994

ƒ₃=−0.1402

The value corresponding to bin ƒ₁ is positive or negative depending onthe BPSK data value of the wave having frequency ƒ₁.

Each frequency is expressed by:

ƒ_(n)=ƒ₀ +nƒ _(s)

where ƒ₀ is an offset frequency and ƒ_(s) is a shift frequency. In somecases it was found that by increasing ƒ₀, the values corresponding toundesired bins were reduced. Various mathematical relationshipsinvolving ƒ₀, ƒ_(s), and/or n may be used to enhance the magnitude ofthe ratios of desired values to undesired values.

In order to measure complex values for each bin, in-phase andquadrature-phase step functions are used:

${{Re}\left( y_{p} \right)} = {\sum\limits_{k = 0}^{K - 1}{x_{k}{\Gamma \left\lbrack {{\tau_{n} = {1/f_{n}}},{\varphi = 0}} \right\rbrack}}}$${{Im}\left( y_{p} \right)} = {\sum\limits_{k = 0}^{K - 1}{x_{k}{\Gamma \left\lbrack {{\tau_{n} = {1/f_{n}}},{\varphi = {\pi/2}}} \right\rbrack}}}$

In order to sample CI waves at a particular phase space φ_(m), a set ofstep functions corresponding to each of the carriers for that particularphase space may be used:

$C_{m} = {{y_{p}\left( \varphi_{m} \right)} = {\sum\limits_{n = 1}^{N}{\sum\limits_{k = 0}^{K - 1}{x_{k}{\Gamma \left\lbrack {{\tau_{n} = {1/f_{n}}},{\varphi = \varphi_{m}}} \right\rbrack}}}}}$

The values obtained for each frequency bin may optionally be multipliedby one or more complex weights w_(n) prior to combining in order tocompensate for fading and/or interference:

$C_{m} = {{y_{p}\left( \varphi_{m} \right)} = {\sum\limits_{n = 1}^{N}{w_{n}{\sum\limits_{k = 0}^{K - 1}{x_{k}{\Gamma \left\lbrack {{\tau_{n} = {1/f_{n}}},{\varphi = \varphi_{m}}} \right\rbrack}}}}}}$

Without, the complex weight w_(n), the result is similar to a simplematched filter that is matched to a CI pulse.

FIG. 82 shows a step function 8211 of a particular phase spacesuperimposed over three sinusoidal waves 8201, 8202, and 8203characterized by different phases of the same frequency ƒ_(n). A firstsinusoid 8201 has the same phase as the step function 8211. The othertwo sinusoidal waveforms 8202 and 8203 contribute interfering terms tothe desired value obtained in frequency bin ƒ_(n) from the firstwaveform. Similarly, at other frequencies, waveforms corresponding tointerfering phase spaces (such as waveforms 8202 and 8203) contributeinterfering terms. However, the sum of bin values over all of thefrequencies corresponding to a desired phase space results indestructive combining of the interference from other phase spaces andconstructive combining of the desired signal.

The table shown in FIG. 83 illustrates the summed values of threefrequency bins of a three-carrier signal generated for a desired phasespace and for the two remaining undesired phase spaces. A set ofquasi-orthogonal phase spaces may be employed. However, this results insome cross correlation between the first set and the second set of phasespaces.

FIG. 84 illustrates basic components of a CI-OFFT receiver. A receivedsignal is optionally processed by a band limiting filter 8401 to limitthe frequency band of the signal. The band limiter 8401 may act as ananti-aliasing filter and/or a channel selector. Received signals areprocessed by a sampler 8402 adapted to generate one or more sample setswith respect to step-function characteristics provided by astep-function generator 8408. The step-function generator 8408 maycontrol one or more sampling parameters of the sampler 8402, such assample width, sample shape, number of samples, sampling interval, samplegrouping, sample-set size, etc. Sample parameters may be adapted toprovide filtering.

Samples generated by the sampler 8402 may optionally be stored in astorage device 8403, such as computer memory. A selector/accumulator8404 selects and groups samples in a combining process. Asymbol-interval selector 8409 may control selection criteria, such assymbol duration T_(s) and number of samples per symbol interval. Thesymbol duration T_(s) corresponds to a particular number ofstep-function periods over which samples are combined. In an OFFTprocess, the combination of symbol durations and step-function periodsare adapted to decompose a received signal into orthogonal components.The resulting signals may optionally be coupled to a processor 8405adapted to perform one or more receiver processes. In some cases, theorthogonal components may be combined in a combiner (not shown).

In an alternative embodiment of the invention, the sampler 8402 providesunformatted samples to the selector/accumulator 8404. Theselector/accumulator 8404 is adapted to generate one or more sample setswith respect to step-function characteristics provided by thestep-function generator 8408. In this case, the selector/accumulator8404 may control symbol duration T_(s) (i.e., carrier separation ƒ_(s))and step-function frequency (i.e., carrier selection). Theselector/accumulator 8404 may optionally provide weights to the samples(such as to adapt to step-function levels, compensate for channeleffects, mitigate interference, perform demodulation, and/or provide forany other signal-processing objectives). The selector/accumulator 8404may optionally discard or replace sample values that exceed and/or fallbelow a predetermined threshold power level.

The principles of the OFFT may be applied to any algorithmic ornumerical implementation of a Fourier transform. Computations in OFFTalgorithms and/or inverse-OFFT algorithms may exploit symmetry and/orperiodicity properties of one or more step functions, such as stepfunction Γ(t). Such computations used to simplify transform operationsare known as divide-and-conquer techniques. Any of various types ofradix-2 and/or radix-4 algorithms may be employed in OFFTs and/orinverse OFFTs. The principles described herein may be applied to oradapted to any of the fast Fourier transforms. The principles describedherein may be applied to any inverse Fourier transform.

The principles of CI Sampling and it applications to digital filteringare fundamental in nature. Step functions (which may take the form ofintegrators, accumulators, recursive structures, adders, storagesystems, etc.) or equivalent functions having harmonic content are usedto process band-limited signals. Step-function processing is simpler toimplement in the time domain than sinusoid-based processing. Bandlimiting allows step functions having appropriate harmonic content toreplace sinusoids in a variety of signal-processing applications.Accordingly, CI sampling may be implemented in a variety of algorithmsand applications, including, but not limited to, sigma-delta modulation,correlation, convolution, resonant filters, sinc filters, invertibletransform operations, frequency conversion, filter banks, andanalysis/synthesis filters.

Inverse CL-OFFT

In an inverse CI-OFFT process, data symbols are impressed onto one ormore carrier signals by generating time-domain symbols that are summedrelative to a function representing a sum of a plurality of valuespertaining to at least one orthonormal basis. In one embodiment, theorthonormal basis values in the function's sum include only one carriersin a multicarrier signal. In another embodiment, the orthonormal basisvalues in the function's sum include more than one carrier in themulticarrier signal.

In one specific example of the invention, data symbols are impressedonto one or more carrier frequencies of a multicarrier signal bycombining one or more information symbols relative to a step functionhaving one or more frequencies. The periodicity of each step functionpreferably corresponds to a frequency of the multicarrier signal. Insome applications, the multicarrier frequencies correspond to one ormore harmonics of one or more step functions.

Step-function values may include at least two of the following set ofnormalized values: 1, 0, and −1. Alternatively, the step function valuesmay be derived from a constellation of more than two values.Step-function values may be incremental or non-incremental.

FIG. 85 illustrates a plurality of five-level step functions 8501 to8509. The step-function frequencies are orthogonal over the intervalshown. FIG. 86A illustrates a pulse 8601 resulting from a superpositionof the step functions 8501 to 8509. In one case, high-frequencycomponents of the superposition pulse 8601 may be filtered using alow-pass filter (not shown) to produce a filtered baseband pulse 8602illustrated in FIG. 86B.

Step functions may be modulated with at least one information signal toproduce an information-modulated pulse. In one application, each stepfunction is modulated (or otherwise impressed) with at least oneinformation signal. The step functions may be modulated via CI coding.In one example, the step-function carriers are provided with a pluralityof interfering information signals and the carriers are combined toproduce a plurality of superposition pulses that characterize each ofthe information signals. In some applications, the carriers may beprovided with phase offsets (for example, to enhance security and/orreduce PAPR) prior to combining. Low-frequency and/or high-frequencycomponents of the combined signals may be selected and/or removed viafiltering. In one set of applications, selection of high-frequencycomponents of the combined signals may provide for frequencyup-conversion.

FIG. 87A illustrates a combined signal 8701 resulting from asuperposition of a plurality of step functions having a frequency offsetƒ₀. FIG. 87B illustrates a low pass filtered superposition signal 8702after high-frequency components have been removed from the combinedsignal 8701.

FIG. 88A illustrates a superposition pulse 8801 generated from aplurality of binary step functions (not shown). FIG. 88B illustrates afiltered superposition pulse 8802 generated by low-pass filtering thepulse 8801.

FIG. 89A illustrates a functional embodiment of an inverse CI-OFFTsystem of the invention. Information symbols from an input informationstream are modulated by a modulator 8901 onto a plurality of stepfunctions generated by a step-function generator 8904. The stepfunctions may be weighted by an optional weight generator 8905 prior tobeing combined in a combiner 8902. The step functions may be weighted toprovide coding (such as to provide carrier-phase offsets and/or toimplement a direct-sequence type of coding), compensate for channeldistortion, generate array-processing weights, or perform any otherphysical-layer processing. The combined signal may be filtered toprovide a band-limited signal and/or provide for frequencyup-conversion. The filtered signal is optionally provided to atransmission system (not shown) for coupling into a communicationchannel.

FIG. 89B illustrates an alternative functional embodiment of an inverseCI-OFFT system. A weight generator 8911 is adapted to provide weights toa step-function generator 8912. The weights characterize at least oneinformation signal. Optionally, the weights may be adapted to otherphysical-layer parameters, such as coding, channel compensation,array-processing weights. The weighted step functions are combined in acombiner 8913 and filtered by a filter 8914 prior to being coupled to atransmission system (not shown).

FIG. 89C illustrates yet another embodiment of a functional embodimentof an inverse CI-OFFT system of the invention. An information stream isprocessed by a serial-to-parallel converter 8921. The informationsymbols are combined in a combiner 8922 with respect to a plurality offunctions, such as provided by a step-function generator 8924.Optionally, the information symbols may be weighted and/or combined withrespect to weights provided by a weight generator 8925. The combinedsignals are processed by a filter 8923 prior to being coupled to atransmission system (not shown).

The methods and systems illustrated with respect to OFFT techniques(including inverse CI-OFFT) may be interpreted in many different ways.Signals may be generated and combined in many different ways withrespect to OFFT techniques. Data symbols may be processed in manydifferent ways that are analogous to step-function generation andcombining techniques associated with OFFT techniques.

CI-Based Wavelets

In B. B Hubbard's The World According to Wavelets (2^(nd) edition, A KPeters, Ltd., Natick, Mass., 1998), which is hereby incorporated byreference, the FFT is described as “the modern algorithm that has mosttransformed our society.” Gilbert Strang states “whole industries arechanged from slow to fast by this one idea.” The primary advantage ofthe FFT is that it reduces the computational complexity relative to theDFT. For example, the FFT reduces the number of complex multiplicationsfrom N² to NlogN. CI applications to Fourier transforms, as describedherein, provide even more substantial reductions in complexity.

The Fourier transform provides a useful interpretation of the manyphysical phenomena. For example, the realization that an elementaryparticle does not simultaneously have a precise position and a precisemomentum is a natural consequence of Fourier analysis. One of theprinciple arguments supporting wavelets is that Fourier analysis ispoorly suited for brief signals or signals that change in time.Drawbacks to Fourier analysis are based on the observation that sincethe building blocks of Fourier analysis are sines and cosines thatoscillate for all time, Fourier analysis is not effective in describingsignals having changing frequencies.

A windowed Fourier transform may be used to analyze a signal in bothtime and frequency by detecting frequencies of the signal in each of aplurality of time segments. The windowed Fourier transform replaces theFourier transform's sinusoidal wave with a product of a sinusoid and awindow function that is localized in time. However, small windows areblind to low-frequency components of the signal and large windows do notprovide adequate time resolution.

Many parallel interpretations can be made between the Fourier transformand other transforms. For example, the discreet wavelet transform isanalogous to the DFT. Consequently, aspects of the present inventionpertaining to Fourier transforms can be extended to variations of theFourier transform and other transforms as well. Transforms and inversetransforms that may be used in conjunction with the present inventioninclude, but are not limited to, Abel, Bessel, Fourier, Haar, Hadamard,Hankel, Hartley, Hilbert, Hough, Laplace, Mellin, Radon, Slant, Walsh,Wavelet, and Weber transforms.

The wavelet transform replaces the Fourier transform's sinusoidal waveswith a wavelet-window family generated by translations and dilations.The continuous wavelet transform (CWT) is expressed by:

γ(s,τ)=∫f(t)Ψ*_(s,τ)(t)dt

The CWT equation illustrates how a function ƒ(t) is decomposed into aset of wavelet basis functions Ψ_(s,τ)(t). Optionally, the wavelet basisfunctions Ψ_(s,τ)(t) may be expressed by one or more sets of CI basisfunctions. The variables s and τ are scale and translation,respectively. The inverse wavelet transform is given by:

f(t)=∫∫γ(s,τ)Ψ_(s,τ)(t)dτds

The wavelets are generated from a single basic wavelet by scaling andtranslation:

${\Psi_{s,\tau}(t)} = {\frac{1}{\sqrt{s}}{\Psi \left( \frac{t - \tau}{s} \right)}}$

When discreet wavelets are used to transform a continuous signal, theresult is a series of wavelet coefficients. It is preferable that thediscreet wavelets behave like an orthonormal basis. Selection of thebasic wavelet can make discreet wavelets substantially orthogonal totheir dilations and translations:

${\int{{\Psi_{j,k}(t)}{\Psi_{m,n}(t)}{t}}} = \left\{ \begin{matrix}{1,{j = m},{k = n}} \\{0,{otherwise}}\end{matrix} \right.$

An arbitrary signal can be constructed from a sum of the orthogonalwavelet basis functions weighted by wavelet transform coefficients:

${f(t)} = {\sum\limits_{j,k}^{\;}{{\gamma \left( {j,k} \right)}{\Psi_{j,k}(t)}}}$

A set of orthogonal code vectors can be obtained from rows and/orcolumns of the matrix Ψ_(j,k)(t).

In addition to using the orthogonal wavelet basis to define orthogonalcode vectors, the orthogonal basis functions may be defined as carriersin the definition of CI. For example, multiple orthogonal basisfunctions may be modulated with the same data symbol with respect to oneor more CI codes. Multiple CI encoded data symbols may each modulate themultiple orthogonal basis functions with respect to an orthogonal phasespace. In this context, a phase space is defined as a set of signalparameters (such as phases) that allow signals impressed onto the sameset of carriers to be separated via interferometry.

CI can provide a multicarrier basis to wavelets. Thus, CI can be used toprovide multi-resolution analysis to analyze one or more signals atdifferent frequencies with different resolutions. CI-based pulses can beused to provide good time resolution and poor frequency resolution athigh frequencies and good frequency resolution and poor time resolutionat low frequencies. This approach is useful when the signal beinganalyzed has high frequency components for short durations and lowfrequency components for long durations.

A CI-based wavelet is represented by a superposition of finite-durationCI waveforms, such as sinusoids. The duration of a CI wavelet may equalthe symbol duration T_(s)=1/ƒ_(s) or some fraction of T_(s). Waveletfunctions with different regions of support that are used in atransformation process can be derived from one a CI-based function.Translation is related to phase space, as a pulse position is defined bya unique set of sub-carrier phases. Scaling is related to the inverse ofa CI pulse's effective carrier frequency ƒ_(eff). The effective carrierfrequency ƒ_(eff) may be adjusted by appropriate selection and/orweighting of individual CI carrier frequencies ƒ_(n) or selection of theoffset frequency ƒ₀. Similarly, the CI-based mother wavelet may bechanged simply by adjusting carrier selection and/or carrier weighting.Because wavelets can be expressed as a linear combination of CIsub-carriers, various sub-carrier groups may be used as basis vectorsfor wavelets.

CI wavelets having various scales and translations are multiplied with asignal being analyzed. The product is nonzero where the signal falls inthe region of support of the wavelet, and it is zero elsewhere. Eachproduct represents a superposition of correlation values of a given setof CI subcarrier basis functions having complex weights corresponding toa particular CI wavelet. By shifting the wavelet in time, the signal islocalized in time, and by changing the scale, the signal is localized ineffective frequency f_(eff).

The wavelet transform has good time and poor frequency resolution athigh frequencies, and good frequency and poor time resolution at lowfrequencies. However, a high-frequency (i.e., small scale) CI-basedwavelet can be decomposed into a plurality of narrowband sub-carriercomponents to provide high frequency resolution. Similarly, multiplelow-frequency (i.e., large scale) wavelets can be combined relative toat least one predetermined phase space to provide a superposition signalcharacterized by high time resolution.

Required sampling rates correspond to CI sub-carrier frequencies. Atlower frequencies, the sampling rate can be decreased, which saves aconsiderable amount of computation time. Nyquist's sampling rate is theminimum sampling rate that allows the original continuous time signal tobe reconstructed from its discrete samples. Discretization can be donein any way without any restriction as far as the analysis of the signalis concerned. If synthesis is not required, even the Nyquist criteriadoes not need to be satisfied. The restrictions on the discretizationand the sampling rate become important if, and only if, the signalreconstruction is desired.

FIG. 90 illustrates a wavelet 9000 constructed from a plurality of CIcarriers, such as CI carriers 9001 to 9007. CI carriers may be used toconstruct any wavelets, including, but not limited to, Morlet, Mexicanhat, Meyer-Lemarier', Daubechies, and Malvar wavelets. CI wavelets mayinclude various types, including continuous, discreet, frame, orthogonaltransform, quasi-orthogonal transform, and bi-orthogonal transformwavelets.

In the case of a continuous transform, any function having a zerointegral can be a wavelet. A feature of orthogonal CI carriers that isexploited by the present invention is that each carrier has a zerointegral. Thus, the CI carriers can be implemented as sinusoidal basisfunctions for any wavelet.

Orthogonal wavelets are a special case of discreet wavelets. Orthogonalwavelets provide a representation of a signal without redundancy andlend themselves to fast algorithms. CI-based wavelets can beorthogonalized with respect to phase space, scaling, and/or frequencyshift. Orthogonal CI wavelets may share the same carriers and thecarrier phases may allow the wavelets to be orthogonal. CI carrierweights may be adjusted to generate different wavelet types, adjustscaling, and/or provide time shifts. CI-based wavelets can also beprocessed via fast algorithms, including FFTs, OFFTs, wavelettransforms, and CI sampling algorithms.

FIG. 91 illustrates a Morlet wavelet packet 9100 that represents asuperposition of CI carriers, such as CI carriers 9101 to 9107. Inconventional wavelet systems, a wavelet packet represents a product of awavelet and an oscillating function. The wavelet part is responsive toabrupt changes and the oscillating function reacts to regularoscillations. The packet width, frequency, and position can each bevaried independently. The CI packet 9100 width can be varied byadjusting CI carrier 8602 weights. The oscillating function in the CIwavelet packet 9100 may be represented by an effective carrier frequencyƒ_(eff). Techniques for selecting and adjusting the effective carrierfrequency ƒ_(eff) are described throughout the specification. In someapplications, a carrier-frequency offset ƒ₀ may be provided to the CIcarrier frequencies ƒ_(n) to select or adjust the effective carrierfrequency ƒ_(eff). The CI packet 9100 position can be shifted byshifting the carrier phase space.

FIG. 92A illustrates three overlapping CI pulses 9201, 9202, and 9203.The oscillations in the pulses 9201, 9202, and 9203 have frequencies ƒ₁,ƒ₂, and ƒ₃, respectively. The pulses 9201, 9202, and 9203 combine toprovide a superposition signal 9210 shown in FIG. 92B characterized byan approximately linear frequency ramping from ƒ₁ to ƒ₃.

The oscillation in a CI pulse is referred to as an effective carrier.The effective carrier frequency ƒ_(eff) is related to the weightedaverage of carrier frequencies that comprise the CI pulse. The amplitudeof pulse 9201 is near its maximum at time t₁, whereas the amplitudes ofpulses 9202 and 9203 are near zero. Thus, the oscillation frequency ofpulse 9210 is approximately ƒ₁ at time t₁. The amplitude of pulse 9201tends toward zero and the amplitude of pulse 9202 approaches its peakvalue as the time approaches t₂. Thus, the oscillation frequency ofpulse 9210 smoothly transitions from ƒ₁ to ƒ₂ over the time period of t₁to t₂. The amplitude of pulse 9202 drops toward zero and the amplitudeof pulse 9203 increases over the period of t₂ to t₃. Consequently, theoscillation frequency of pulse 9210 smoothly transitions from ƒ₂ to ƒ₃.

FIG. 92C illustrates a plurality of CI carriers 9220 to 9229 thatcombine to generate the superposition signal 9210 shown in FIG. 92B. Thecarriers 9220 to 9229 are characterized by predetermined frequencies,frequency separations, magnitudes, and phases necessary to produce asuperposition signal (such as signal 9210) having predeterminedtransient features. In some applications, time-varying weights may beapplied to the carriers.

A first group of carriers 9220, 9221, 9222, and 9223 combine to generatea portion of the superposition signal 9210 that is characterized byfrequency ƒ₃. A second group of carriers 9224, 9225, and 9226 combine togenerate a portion of the superposition signal 9210 that ischaracterized by frequency ƒ₂. A third group of carriers 9227, 9228, and9229 combine to generate a portion of the superposition signal 9210 thatis characterized by frequency ƒ₃. Transition regions of signal 9210between the frequencies ƒ₁, ƒ₂, and ƒ₃ are characterized by varyingproportions of superposition signals relative to the carrier groups. Insome cases, one or more carrier sets may provide non-negligiblecontributions across most of a superposition signal and/or to aplurality of non-contiguous sections of a superposition signal.

Time offsets of various features of the superposition signal 9210 arecharacterized by one or more carrier phase offsets. The scale of thesuperposition signal corresponds to a scale factor associated with thecarriers. Amplitude variations in the superposition signal 9210 maycorrespond to a set of carrier phases and/or magnitudes. Consequently,time offsets and scales in wavelet processing can be represented bycorresponding CI carrier phase offsets and/or amplitudes. Correlationvalues corresponding to particular wavelets (indicated by scale, offset,and wavelet type) may be converted to correlation values correspondingto one or more predetermined CI carriers. A wavelet interpretation oftransmitted and/or received signals may be conveyed as a CIinterpretation. Conversely, CI interpretations may be converted towavelet interpretations.

FIG. 93 illustrates a conversion between a set of wavelet parameters(τ_(n), s_(n)) to a set of CI parameters (ƒ_(n), w_(n)). A wavelet 9301is characterized by a time offset τ_(n) and a scale s_(n). The wavelet9301 is also characterized by a superposition of CI carriers 9302 havingpredetermined frequencies ƒ_(n) and corresponding carrier weights w_(n).

In some applications, a correlation value associated with a particularwavelet may be expressed by a set of weighted carriers. If multiplewavelets are generated from the same set of carriers, each waveletcorrelation value maps into the same set of carriers. Each of thecorresponding carrier weights can be derived from a superposition ofweighted wavelet correlation values. Prior to superposition of theweighted wavelet correlation values used to generate a carrier weightcorresponding to a particular carrier frequency ƒ_(n), each waveletcorrelation value is weighted with the carrier weight w_(n) of carrierfrequency ƒ_(n) associated with the corresponding wavelet.

FIG. 94A illustrates a CI-based wavelet (i.e., superposition signal)9400 characterized by a high time resolution (i.e., a narrow time-domainsignal). FIG. 94B illustrates a plurality of narrowband CI carriers 9401to 9407 that are components of the superposition signal 9400 shown inFIG. 94B. FIG. 94C is a frequency-domain illustration of the carriers9401 to 9407 shown in FIG. 94B. Each frequency-domain component 9401 to9407 is characterized by high frequency resolution (i.e., a narrowfrequency-domain signal). Consequently, a CI-based wavelet provides themeans to perform analysis with high resolution in both the time andfrequency domains.

The inverse relationship between time and frequency illustrated by theFourier transform exemplifies the Heisenberg Uncertainty Principle.However, interferometry methods of the present invention exploit phasespace to circumvent the inherent resolution trade offs between coupledmeasurements, such as time and frequency. Consequently, theinterferometry techniques of the present invention may be extended tovarious probability-distribution applications. These applications mayinclude various types of sensing and analysis.

FIG. 95A illustrates a portion of a particular signal 9500 characterizedby multiple frequencies and transient signal characteristics. Each of aplurality of narrowband CI signals 9501.1 to 9501.N shown in FIG. 95B iscorrelated (or similarly processed) with the signal 9500 to provide aplurality of correlation values c₁(ƒ₁) to c_(N)(ƒ_(N)).

Each correlation value c₁(ƒ₁) to c_(N)(ƒ_(N)) provides a measure ofcorrelation between the signal 9500 and one of the CI signals 9501.1 to9501.N. In some applications, each narrowband CI signal 9501.1 to 9501.Nincludes in-phase and quadrature-phase components. Similarly, thecorrelation process may include in-phase and quadrature phaseprocessing. The correlation values c₁(ƒ₁) to c_(N)(ƒ_(N)) may includeany combination of in-phase and quadrature-phase correlation values. Insome cases, each correlation value c₁(ƒ₁) to c_(N)(ƒ_(N)) may includeseparate in-phase and quadrature-phase components.

FIG. 95C illustrates a superposition signal 9502 resulting from a sum ofthe CI signals 9501.1 to 9501.N. The superposition signal 9502 ischaracterized by a pulse bounded by a narrow time interval Δt=t₂−t₁. AΔt-width signal 9503 illustrates the portion of the signal 9500 thatcontributes substantially to a correlation value resulting from acorrelation between superposition signal 9502 and signal 9500.

An n^(th) correlation value c_(n)(ƒ_(n)) characterizes the presence of acorresponding narrowband frequency components over a relatively longtime interval t′₁−t′₂. The correlation values c₁(ƒ₁) to c_(N)(ƒ_(N)) maybe combined to produce a combined correlation valuec(t₁:t₂)=Σc_(n)(ƒ_(n)). When the correlation values c₁(ƒ₁) toc_(N)(ƒ_(N)) are combined, contributions of signal 9500 outside of thetime interval Δt=t₂−t₁ substantially cancel. Contributions of signal9500 within the time interval Δt=t₂−t₁ combine substantially in phase.

In some applications, complex-valued weights may be provided to thecorrelation values c₁(ƒ₁) to c_(N)(ƒ_(N)) prior to combining. Theweights may be provided to select predetermined time intervals Δt,time-interval width, and/or effective superposition signal 9502 shape.The correlation values c₁(ƒ₁) to c_(N)(ƒ_(N)) may be generated withrespect to some filtering function, such as an FFT.

A CI-based wavelet may be provided with the transmission and/orreception benefits of a multicarrier signal. CI processing, as describedthroughout the specification and in the documents incorporated byreference, may be performed with respect to CI-based wavelets.

FIG. 96A illustrates one aspect of the invention in which waveletparameters (such as scale factors, translations, and/or wavelet type)are modulated or otherwise impressed onto CI signals for transmission.The wavelet parameters are generated 9601 or otherwise acquired prior tobeing used to shape a CI waveform in a step of providing CI symbols withwavelet parameters 9602. The wavelet parameters may be used to shape oneor more CI superposition signals and/or adjust CI symbols that areconveyed on one or more diversity parameters. The CI signals areprocessed for transmission 9603. This processing 9603 typically includespreparing a baseband or IF signal for coupling into a communicationchannel. The transmission-processing step 9603 may include predistortionprocessing, channel selection, coding, interleaving, up conversion,filtering, amplification, mixing, and/or any other processes typicallyperformed prior to transmission.

FIG. 96B illustrates an alternative method of transmitting waveletparameters over a communication channel. Wavelet parameters are providedin a wavelet-generation step 9601. The wavelet parameters are convertedto CI carrier weights using an appropriatewavelet-parameter-to-CI-carrier-weight conversion 9604. The waveletparameters may be CI encoded. The CI symbols representing the waveletparameters are processed in a transmission-processing step 9605 prior tobeing coupled into a communication channel (not shown). In this case,the CI weights may be conveyed via CI transmission signals or any otherform of transmission signaling.

FIG. 96C illustrates yet another method of conveying wavelet parametersas a CI-based signal. Wavelet parameters are provided (i.e., generatedand/or acquired) in a wavelet-generation step 9601. The waveletparameters or wavelets generated with respect to the wavelet parametersare converted to CI waveforms in a conversion step 9606. The CIwaveforms are processed in a transmission processing step 9603 prior tobeing coupled into a communication channel.

In digitally implemented CI systems, synthesis of a superposition of thevarious modulated carriers may be performed via a mathematicaltransformation that generates a sequence of numbers representing theamplitude of the signal as function of time. For example, asuperposition signal may be generated by applying an inverse Fouriertransformation to a symbol vector generated from CI symbols to betransmitted. Similarly, the symbols are recovered at a receiver usingthe corresponding inverse transformation. In addition to receiving andseparating multicarrier signals with a filter bank, a transceiver canperform transmit-side operations (e.g., modulation, multiplexing, etc.)using a digital filter bank.

The computational workload inherent in synthesizing and analyzing amulticarrier signal is related to the number of subbands. For example,if fast Fourier transforms are employed, the workload is of order NlogN,where N is the number of sub-bands. Similar relationships exist forother transforms. Thus, in some applications it is advantageous tominimize the number of subbands. Sub-band selection may be made withrespect to channel estimation. For example, characteristics, such ascoherence length, may be used to optimize sub-channel (i.e., CI carrier)bandwidth(s) and spacing. Other technical considerations, such asinterference, transmitter complexity, receiver complexity, transceiverpower, transmitted power density, etc., may be used to determinesub-channel parameters.

At the receiver, the signal from the communication link may be decodedby a plurality of finite impulse response (FIR) filters that are matchedto the transmitted waveforms. Synchronization errors between thetransmitter and receiver may be corrected with weights determined fromtransmitted training signals. The receiver may include aphase-compensation circuit that includes a second bank of FIR filtersthat measure the amplitude of each carrier after the signal has beenphase shifted.

Various types of filter banks may be implemented. For example, filterbanks may be constructed with narrow-band lapped transforms. Any type ofmatched filter and/or correlator may be implemented. The decompositionof a signal into frequency subbands may be performed by atree-structured filter. Such a filter includes two or more levels offilter banks that can be adapted to implement a time-domain tofrequency-domain transformation. To implement a variable-channel-widthsystem, a transformation that breaks the available frequency band intosubbands of differing width is required. This may be performed using anon-uniform filter-bank transform.

The reverse transformation can be performed by an analogous filter bank.A multi-level tree filter may perform the frequency-domain totime-domain transformation. The symbols to be sent on the finer subbandsare first combined using a first set of synthesis filters to providesignals representing the larger subbands. These symbols, together withthose from other bands, are then combined by a synthesis filter toprovide the time-domain signal that is sent on the communication link.

FIG. 97A illustrates a CI reception method of the invention. Ageneration step 9701 provides for the generation of a plurality of CIcarriers. The carriers are correlated with at least one receive signalto produce one or more correlation values in a correlation step 9702. Anoptional combining step 9703 may be provided to combine a plurality ofcorrelation values.

In the generation step 9701, CI carriers may be provided with in-phaseand quadrature-phase components. The CI carriers may be provided withone or more phase spaces. The CI carriers may be provided with complexweights to compensate for channel distortions. Carrier weights may beprovided to compensate for interference. In some applications employingreceiver arrays, carrier weights may be provided for beam forming. Inany of these cases, the carrier weights may be adaptive.

The correlation step 9702 may include correlating each CI carrier withone or more received signals. In one set of embodiments, the correlationstep 9702 may be adapted to provide correlation between a superpositionof the CI carriers and the received signal. Superpositions of the CIcarriers may take the form of one or more wavelets. CI carrier weightsmay correspond to various wavelet scales, translations, and/or shapes(i.e., wavelet types). The CI-based wavelets may include orthogonalwavelets.

In some embodiments of the invention, the received signal may beseparated into CI carriers prior to correlation. Carrier weights may beprovided to received-signal carriers to compensate for interference andother channel effects. Carrier weights may be provided for beam forming.Correlation, or equivalent processes, may be performed via equivalentprocesses, including, but not limited to, summing samples over apredetermined time interval, weighting and combining samples,sample-and-accumulate processes, etc.

FIG. 97B illustrates an alternative CI reception method. A receivedsignal is decomposed into a plurality of CI components in adecomposition step 9711. The CI components may be processed in anoptional channel-compensation step 9712. Processing may includeproviding complex weights to the CI carriers. The CI components arecorrelated with a CI reference in a correlation process 9713 or someequivalent process. In the case in which multiple correlation values aregenerated by the correlation process 9713, the values may optionally becombined in a combining process 9714. Combining may include providingweights to the correlation values.

FIG. 97C illustrates steps of a CI reception method. A decompositionstep 9721 provides for decomposition of at least one received signalinto a plurality of frequency components, such as CI signals. Thedecomposition step 9721 may provide a plurality of oscillating signalscharacterized by predetermined frequency and bandwidth values. Thefrequency components may be characterized by complex values thatindicate magnitude and phase. The frequency components may includeorthogonal and/or quasi-orthogonal components. The frequency componentsmay include overlapping and/or non-overlapping components.

Channel compensation weights may optionally be provided to one or morefrequency components in a channel-compensation step 9722. CI weights mayoptionally be provided to the components in a weighting step 9723. CIweights may be provided to the frequency components to select aparticular phase space in a combining step 9724. The combining step 9724may include adaptive combining.

Adaptive reception and transmission techniques pertaining to CI wavelets(as well as CI in general) may be based on blind-adaptivefrequency-domain reception. Various reception techniques may be employedto exploit frequency selectivity that affects multiple carriers in amultipath environment. The technique is blind in the sense thattransmitted carrier symbols (e.g., carrier weights) may be unknown.Received carrier symbols may be estimated without calibration andfeedback. In one set of receiver embodiments, optimal combining (i.e.,an optimal beam pattern in the frequency domain) is based on certainstatistical properties of the received signals. Optimal combining isperformed by solving an optimization equation.

FIG. 98 illustrates a CI transceiver of the invention. A receiver system9801 couples a transmitted signal out of a communication channel (notshown). One or more typical receiver-side signal processing techniques(including filtering, mixing, down conversion, amplification, A/Dconversion) may be performed on the received signal. A filter bank, suchas an FFT 9802, separates the received signal into a plurality offrequency components. The components are provided with weights in areceiver weighting system 9803. The weights may include one or moretypes of weights, such as channel-compensation weights, decodingweights, demultiplexing weights, MUD weights, array-processing weights,wavelet-processing weights, etc. The weighted carriers are combined in acombiner 9804. The combined signals may be processed in a data processor9805. The data processor 9805 may be part of a blind-adaptive processor9806 that is adapted to generate and/or adapt weights relative to one ormore performance parameters, including channel estimates, confidencemeasures, data estimates, signal power, probability of error, BER, SNR,and SNIR.

In one embodiment of the invention, the blind-adaptive processor 9806 isadapted to process a plurality of information-bearing CI symbolsproduced from a plurality of carriers. The processor 9806 may work inconjunction with the combiner 9804 to combine the carriers and estimatetransmitted data. The combining process may include wavelet processing.The processor 9806 may work in conjunction with the data processor 9805to provide a channel estimate based on the data estimate. The processor9806 may employ a time-varying channel-estimation filter (not shown).The processor 9806 provides channel compensation to the received CIcarriers and/or symbols. Channel compensation may be based on astatistical characterization of interference, such as a covariancematrix.

In some applications, the processor 9806 may provide predistortionweights to transmitted carriers. A data stream is optionally processedby a transmit data processor 9807. The data processor 9807 may performwavelet processing. A transmitter weighting system 9808 is adapted toweight data symbols provided to frequency bins of afrequency-domain-to-time-domain converter, such as an IFFT 9809.Time-domain signals generated by the IFFT 9809 are provided to atransmission system adapted to prepare the time-domain signals fortransmission into a communication channel.

Wavelets, such as CI wavelets, may be used to convey data symbols, codesymbols, etc. Symbols may be conveyed via phase shifts, amplitudes,frequencies, polarizations, or any suitable combination of modulationtechniques. Orthogonal wavelets, such as wavelets orthogonalized byscaling and/or time offsets, may be used to convey different datasymbols and/or different communication channels. CI-based wavelets maybe orthogonalized via each wavelet's effective carrier frequency. Datasymbols may be spread over multiple orthogonal wavelets via someappropriate form of coding, such as direct-sequence and/or CI coding.

In some applications, quasi-orthogonal wavelets, such as overlappingwavelets, may be used to convey data symbols and/or communicationchannels. Methods of processing overlapping wavelets may be performed inthe same manner as that overlapping CI waveforms (e.g., CI pulses) areprocessed. Processing may include either or both time-domain andfrequency-domain processing.

Wavelets may be provided with coding using one or more codingtechniques. In one set of applications, each code uses the samewavelets. A code may be provided as a set of phase shifts (e.g., apolyphase CI code or a binary-phase direct-sequence code) or some otherdiversity-parameter values applied to the wavelets. An orthogonalchannel may consist of a set of codes applied to orthogonal orquasi-orthogonal wavelets. In one set of embodiments, the wavelets mayeach have the same duration with orthogonal effective carrierfrequencies applied to the wavelets relative to some code.

In an alternative set of embodiments, each code is composed of aplurality of wavelets having different scales (e.g., durations). Theorder of the wavelets determines each code. In a special case, each codechip has the same duration. The number of wavelets representing eachchip depends on the duration of the particular wavelet compared to theduration of the chip. Orthogonal wavelets may be provided wherein thewavelet scales are related by multipliers that are powers of two.

CI Adaptability

The present invention increases flexibility and adaptability byproviding scaling of operating parameters and/or signal characteristicsin a CI system. FIG. 99 illustrates a control circuit 9901 adapted toprocess one or more system requirements 9911 and, optionally, one ormore channel characteristics 9912. The control circuit 9901 providesadjustment to one or more CI parameters 9902 in a CI transceiver 9903.CI parameter adjustment and/or selection affects one or more transceiveroperating parameters 9921.

The control circuitry 9901 may scale a transmitted bit rate by scalingthe CI symbol duration, the number of carriers, the carrier spacing,and/or the number of bits per symbol per carrier. This permits thescaleable CI system to operate in various communications environmentsrequiring various operating parameters and/or characteristics. Byscaling the operating parameters and/or characteristics of the CI systemwhen control circuitry 9901 determines that different operatingparameters and/or characteristics are necessary or advantageous, thecontrol circuitry 9901 can dynamically change the operating parametersand/or characteristics, thereby providing compatibility or the desiredperformance. For example, dynamically scaling the bit rate enableswidely varying signal bandwidths, adjustment of delay-spread tolerances,and adaptability to different SNR requirements. A scaleable CI system isparticularly suitable for applications in mobile wirelesscommunications, as well as other applications that support a variety ofservices in a variety of environments.

In accordance with aspects of certain embodiments of the scaleable CImodulation system, a CI modulation system can be designed with an upperlimit on the number of carriers and a variable symbol duration. Thecontrol circuitry can dynamically scale the number of carriers below theupper limit to decrease the signal bandwidth and the transmission ratewhile delay-spread tolerance remains the same. The control circuitry 901can also dynamically increase the symbol duration to decrease thetransmission rate and the signal bandwidth and provide an increase indelay-spread tolerance. The control circuitry 9901 may be adapted toadjust the transmission rate by changing the type of modulation. Inaccordance with other embodiments, a scaleable coded CI modulationsystem achieves variable transmission rates using adaptive coding wheredifferent coding schemes are used to improve the link reliability and/orto decrease the peak-to-average power ratio.

In accordance with yet other embodiments of the scaleable CI modulationsystem, scaleable transmission rates permit asymmetric data ratesbetween mobile units and base stations. For example, the mobile unitscan have lower data rates than the base stations by allocating only afraction of the total number of carriers to each mobile, while the basestations transmit on all carriers simultaneously. Additionally, duringdata downloading, for example, a mobile unit could have a largerdownlink data rate than uplink data rate. In accordance with otheraspects of a scaleable CI system, mobile units and base stations usingthe same antennas for both transmit and receive operations can benefitfrom adaptive antennas without any additional processing requirements atthe base station, thereby keeping the mobile units as simple aspossible. The scaleable CI modulation system can use an adaptive antennaat the base by sending feedback through the uplink when uplink anddownlink channel characteristics are not identical.

Power control may be performed by either or both CI transmitters and CIreceivers on each carrier or on subgroups of carriers. Alternative topower control, certain carriers may be selected to optimize one or moreoperational parameters, such as throughput, probability of error,received signal power, transmitter power efficiency, SNR, QOS, etc. CIcarriers may be selected with respect to the types of services beingprovided. For example, different qualities of service corresponding todifferent-priority links and/or different link services may be criteriafor selecting CI carriers. In one case, carriers having littledistortion and interference may be selected for services (such as datalinks) that do not tolerate high BER. In another case, a transmissionmay be divided into sections and sent on two or more groups of carriers.An important section, such as addressing information, may be sent onhigher-quality channels than the channels on which the payload data issent. Addressing and other control information is typically lesstolerant to errors than payload data. Thus, important parts of atransmission may be transmitted on orthogonal phase spaces and/or oncarriers having little distortion and fading.

Another aspect of the invention employs a medium access contention (MAC)protocol that is highly beneficial in wireless networks, andparticularly in CI-based wireless networks that employ a fixed minimumburst size. In one embodiment, a MAC protocol is a demand-assignedprotocol that maximizes utilization of the allocated frequency spectrum(i.e., the bus medium). Each data communication device (DCD) in thenetwork communicates with a central access point (AP). Multiple DCDs mayrequest access from the AP in the same request access (RA) burst. In oneembodiment, each of the multiple DCDs transmits its access request tothe AP within a frequency-domain channel in the RA burst that isorthogonal to the frequency domain channels used by the other DCDsrequesting access. In another embodiment, each of the multiple DCDstransmits its access request to the AP within a phase-space channel inthe RA burst that is orthogonal to the phase-space channels used by theother DCDs requesting access. Alternatively, other orthogonaldiversity-parameter values may be employed. Each DCD includes channeltraining information in the access request burst to allow the AP and/orDCD to adapt to rapid variations in channel characteristics.

Ad-hoc CI Networking

FIG. 100A illustrates a plurality of subscriber units 10001 and 10002(e.g., mobile or fixed subscriber units) in a network having a pluralityof access points 10011 to 10015 (e.g., base stations). At least one ofthe subscriber units 10001 is adapted to transmit a pilot signal orknown training signal that is received at the plurality of access points10011 to 10015. Signal paths 9931 to 9935 corresponding to a pilottransmission from the subscriber unit 10001 and the access points 10011to 10015 are shown. The propagation environment ensures that the set ofpilot signals received by the access points 10011 to 10015 is unique foreach subscriber's location. The uniqueness of the propagationenvironment may be exploited to provide or enhance coding. The accesspoints 10011 to 10015 are adapted to process the received pilot signals.Processing operations may depend on various characteristics of thereceived pilot signals, including absolute and/or relative signal powerlevels. For example, a predetermined number of access points 10011 to10015 may be selected to process signals for a given subscriber unitbased on the received pilot signal power.

At least one of the access points 10011 to 10015 is adapted to performchannel analysis to characterize the propagation environment of thetransmissions between the subscriber unit 10001 and the access point(s).Channel analysis may include delay-profile and/or flat-fadingcharacterizations. The propagation environment may be employed as aunique identifier for each subscriber unit. Channel weights calculatedfrom channel estimates may be utilized in multiple-access codes,encryption codes, and/or authentication and verification procedures.

Channel analysis may be used to generate filter weights and/orarray-processing weights at the access points 10011 to 10015 to processreceived and/or transmitted signals. The access points 10011 to 10015may include single-antenna systems or multi-antenna systems, such asantenna arrays. Received signals may be compared to some local or globaltiming reference, such as to analyze phase offsets and/or signal timing.

FIG. 100B illustrates a plurality of access points 10011 to 10015adapted to transmit channel-compensated signals 9941 to 9945. Thetransmissions 9941 to 9945 exploit the propagation channels between theaccess points 10011 to 10015 and at least one subscriber unit 10001 toconstructively combine at the at least one subscriber unit's 10001location.

In one set of embodiments of the invention, transmission weights aregenerated from the reciprocal of a channel matrix that characterizes thepropagation environment between one or more access points (such asaccess points 10011 to 10015) and the at least one subscriber unit10001. Channel weights may be provided via any combination ofdeterministic (i.e., training) and blind-adaptive processing. Channelweights may be selected and/or adapted to optimize coherent combining ofaccess-point transmissions to one or more subscriber units. Similarly,the channel weights may be selected and/or adapted to optimize coherentcombining of signals received from one or more subscriber units. Any ofvarious optimal combining techniques may be employed.

Channel weights may be adapted to generate beam-pattern nulls at one ormore undesired subscriber units or interference sources (not shown).Channel weights may be adapted to provide time-varying channelcompensation. Thus, beam steering, null steering, or any othertime-dependent adaptive array processing may be performed. Appropriatecombinations of carrier selection and carrier weighting may be providedto achieve simultaneous directionality and diversity benefits. In someapplications, the access points 10011 to 10015 shown may be replaced bysubscriber units acting as routers, relays, and/or array elements of anadaptive transceiver array.

FIG. 101 illustrates a plurality of access points 10011 to 10015connected to a network 10200, such as an optical-fiber or wirelinenetwork. A central processor 10201 is adapted to process signalsreceived and transmitted by the networked access points 10011 to 10015.In this case, the access points 10011 to 10015 may be “dumb terminals,”wherein most or all of the signal processing is performed by the centralprocessor 10201. For example, the central processor 10201 may performchannel analysis and generate access-point weights to optimizecommunication with the subscriber units (not shown). The access points10011 to 10015 may perform only basic signal-processing functions, suchas RF processing and frequency conversion.

The central processor 10201 may provide base-station functionality, suchas power control, code assignments, and synchronization. The centralprocessor 10201 may provide network load balancing, including providingfor balancing transmission power, bandwidth, and/or processingrequirements across the network. Base-station functionality may becontrolled by individual access points or subscriber transceiversassigned to act as base stations. Array processing may be performed in adistributed sense wherein channel estimation, weight calculation, andoptionally, other network processing functions (such as load balancing)are computed by a plurality of spatially separated processors (e.g.,access points and/or subscriber units) adapted to work together. Acentral processor (such as central processor 10201) may optionally beprovided to control data flow and processing assignments throughout thenetwork.

Other types of networks, including wireless networks, may connect theaccess points 10011 to 10015. One or more of the access points 10011 to10015 may be replaced by subscriber units (not shown) adapted to performas routers, repeaters, and/or elements of an antenna array.

In this case, the entire access-point network 10011 to 10015 is adaptedto operate as an antenna array. In most applications, a portion of thenetwork may be adapted to serve a particular subscriber transceiver. Thenetwork may be adapted to perform long baseline interferometry. Thecentral processor 10201 and/or the access points 10011 to 10015 may beadapted to perform other signal-processing operations, such as, but notlimited to, waveform shaping, error detection, error correction, powercontrol, channel selection, multiple access control, multiplexing,modulation, formatting, synchronization, coding, etc. In alternativeembodiments of the invention, the central processor 10201 is replaced bya distributed computing system (not shown) that may reside at aplurality of subscriber units, repeaters, and/or access points.

FIG. 102 illustrates a network architecture in which a plurality ofsubscriber units 10201 to 10205 are adapted to function as routersand/or repeaters. Each network node (e.g., subscriber unit 10201 to10205, access point (not shown), etc.) may be adapted to function as arouter and/or repeater. As the network evolves, the nodes adapt therouting tables to optimize throughput. As network loads change, thenodes perform load balancing to ensure a predetermined range ofbandwidth and transmit-power loads across the network. One or more pathsto each subscriber unit may be selected or modified to optimize loadsacross the network, minimize transmission power, and/or ensure receivedsignal quality. In one aspect of the invention, multiple transmissionpaths to the subscriber units are employed to achieve one or moreobjectives, such as reducing the effects of fading, reducingtransmission power in some of the relays, and/or distributingtransmission power across the network.

Information intended for a particular subscriber unit (e.g., subscriberunit 10210) is passed through the network along a chain of subscriberunits 10201, 10202, and 10203. One or more subscriber units (e.g., units10204 and 10205) provide a final radio link 10224 and 10225 for thetransmission.

The transmission signals may include multiple addresses corresponding toat least one path to the intended subscriber unit(s). The transmissionmay include multiple addresses corresponding to a plurality of devicesthat provide the final RF link to the desired subscriber. Alternatively,the transmission may include only the destination address of the desiredsubscriber. More than one destination address may be included for aparticular transmission. The transmission signal may be duplicated onlywhen the paths diverge. For example, a message with addresses to units10204 and 10205 is duplicated by transceiver 10203. Alternatively, abroadcast message may include a plurality of addresses and the networkmay be adapted to propagate a single version of the message to all ofthe addresses.

In one set of embodiments, a data message is provided that includes aplurality of destination addresses. Processing instructions, such astransmission weight values, may be included in the data message. Asingle copy of the message is routed through nodes that form a path thatis common to all of the destination addresses. The message is duplicatedwhere the paths to the destination addresses diverge. The addresses mayinclude any combination of codes and network header data bits. The codesmay include any combination of polyphase CI codes, CI-based codes, andchannel-specific spatial interferometry codes. For example, the channelcharacteristics for each subscriber may be exploited to provideaddressing and/or multiple-access coding. CI codes may be implementedacross one or more diversity-parameter spaces. Coding may includespace-time coding, space-frequency coding, polarization coding, etc.

In some applications, CI codes may be adapted to accommodate changingnumbers of users, different network topologies, load balancing, andvarying network services. Code lengths, code orthogonality, number ofcodes per transmission, and/or chip values for one or more codes may beadapted. CI codes and/or network header addresses may be adapted tochanging network conditions. In one set of embodiments, one or morenetwork nodes (e.g., transceivers) may be adapted to process apredetermined set of addresses specified by codes and/or headers. Afirewall may be implemented to isolate processing for transmissionsrouted through a transceiver from transmissions that are addressed tothat transceiver. The nodes may perform error detection and/or errorcorrection for each data stream prior to re-addressing andre-transmission.

In another embodiment of the present communication system, everysubscriber has access to every transmitted message. Transmitted signalsmay be routed throughout the entire network. A transmitted message maybe received by more than one unit and may be received while the unit istransmitting. CI coding may be employed to provide multiple access andthus, eliminate conflicts to increase system capacity. Similarly,channel-specific coding may be employed. In one aspect of the currentembodiment, each transmission has a preamble that includes the code,which allows subscribers to synchronize with the transmission.Optionally, a tag may follow the preamble to identify the data payload.

In the current embodiment, each subscriber has access to the communitytransmissions. The system allows each subscriber to dynamically selectfor reception only those transmissions that are relevant to thatsubscriber. Individual subscriber transceivers may be equipped withadaptable or programmable decoders designed to select and decode one ormore transmissions. The transceivers may be provided with a bank ofdecoders to decode and process multiple received signals simultaneously.The system further provides data inter-operability by use of a commonCI-based waveform structure.

In one aspect of the invention, the communication signals are providedas coded sets of low-bandwidth subchannels. Thus, interference resultingfrom multipath and effective multipath due to retransmissions ofinformation through the network is reduced to flat fades. Sub-carrierbandwidths may be adapted to the multipath channel in one or more partsof the network. Coding may be adapted with respect to one or moreparameters, including geographical distributions of subscriber units andaccess points, channel conditions, link priority, security, subscriberservices, number of subscribers, etc.

In one embodiment of the invention, base-station responsibilities areassigned to, or assumed by individual subscriber units. Base-stationoperations are coordinated with simultaneous coded transmissions of acommunications channel and a control channel. Codes may include CIcodes, CI-based coding, channel-specific coding, or any combinationthereof. A time division duplexing method may be employed for transmitand receive operations to implement the necessary control functions foroperation without a base station. Each subscriber unit can be assignedto be a network control station. By using time division duplexing fortransmit and receive operations in a CI-based multiple access system theentire frequency bandwidth can be used, in contrast to base stationoperations having one set of frequencies for transmitting and anotherset of frequencies for receiving.

The subscriber unit that is acting as a network control stationmaintains power control and time synchronization normally performed bythe base station. Power control is maintained within predetermined timeintervals by a feed-back control loop using proportional integration anddifferentiation to smooth control such that power oscillations aremaintained within desired limits. The network control functions mayautomatically be transferred if the connection with the transceiver isterminated or there is a predetermined degree of signal-qualitydegradation. The network control station has channel controlcapabilities to assure transmission security. For example, the networkcontrol station may assign codes to the other subscriber units to changethe security or priority of individual communication links.

FIG. 103A illustrates a CI transceiver adapted to perform routing.Transmitted signals are received by a receiver system 10301 that outputsa baseband signal. The receiver system 10301 performs RF and(optionally) baseband processes typically performed to convert an RFsignal to a baseband or intermediate frequency signal. For example, thereceiver system 10301 may perform channel selection, filtering,amplification, frequency conversion, and A/D conversion.

A CI decoder 10302 is adapted to decode the baseband signal relative toone or more address codes intended for the transceiver. The decoder10302 may select a signal relative to an address in a header prior todecoding. A signal processor 10303 may process the decoded signals priorto producing an output data stream. Signal processing may include one ormore signal-processing operations, including, but not limited to,quantization, channel decoding, multiple access decoding,demultiplexing, formatting, demodulation, channel estimation, channelcompensation, synchronization, filtering, error detection, errorcorrection, signal-quality analysis, multi-user detection, phase-jittercompensation, frequency-offset correction, time-offset correction, etc.

A control system 10304 is adapted to select, adapt, or otherwise controlthe operation of one or more transceiver components. For example,channel estimates and/or signal-quality analysis performed by the signalprocessor 10303 may be processed in the control system 10304 to adaptdecoding performed by the decoder 10302. The control system 10304 mayprovide power control to the transmission system 10306 and/or otherwiseprovide network control. Similarly, CI coding may be adapted by thecontrol system 10304.

A CI coder 10305 is adapted to process input data bits to produce acoded signal that is coupled to a transmission system 10306. Thetransmission system 10306 performs signal-processing operationstypically performed to prepare a baseband signal for transmission into acommunication channel. The transmission system 10306 may perform one ormore processes, including, but not limited to, D/A conversion,modulation, filtering, amplification, frequency conversion, beamforming, etc.

Signals from the receiver system 10301 are coupled to a CI decoder10312, which may include a bank of CI decoders. The decoder 10312decodes received signals that are to be retransmitted. The decodedsignals are processed in a signal processor 10313. The signal processor10313 may perform similar signal-processing operations as signalprocessor 10303. Furthermore, the signal processor 10313 may performpre-processing operations prior to coding in a CI coder 10315. The coder10315 may include a CI coder bank. A control system 10314 is adapted toselect, adapt, or otherwise control the operation of one or more of thetransceiver components 10312, 10313, and 10315.

The control system 10314 and the coder 10315 may providechannel-compensation and/or beam-forming weights to the coded symbols.Such weights may be regarded as part of the routing process. Sincerouting decodes some signals that are not intended for the transceiver,the router components 10312, 10313, 10314, and 10315 are isolated fromthe rest of the transceiver by a fire wall 10310.

Code division duplexing or cancellation division duplexing may beemployed to permit reliable reception while concurrently transmitting.Alternatively, other types of duplexing may be employed. Pseudo-randomtime, frequency, and/or phase codes are typically used to avoidself-jamming. However, CI codes and CI-based waveforms enable thefrequency-domain processing required for optimal performance in amultipath environment while providing data redundancy (i.e., channelcoding) needed to mitigate errors. Optionally, additional channel coding(e.g., block, convolutional, TCM, turbo) may be provided to CI waveformsand/or CI coding.

FIG. 103B illustrates an alternative embodiment of a CI receiver adaptedto perform routing. Many of the system components shown in FIG. 103B aresimilar to components shown in FIG. 103A and thus, are identified bycorresponding reference numbers. A portion of the baseband (or IF)signal(s) produced by the receiver system 10301 is optionally processedin a processor 10319 prior to being coupled into the transmission system10306. The processor 10319 may perform one or more baseband or IFprocesses, including, but not limited to, signal shaping, filtering,re-quantization, error detection, error correction, interferencemitigation, multi-user detection, amplification, up sampling, downsampling, frequency conversion, D/A conversion, AGC, symbol remapping,etc.

FIG. 103C illustrates a CI transceiver adapted to decode receivedsignals intended for the transceiver and partially decode and routesignals intended for one or more other transceivers. System componentsshown in FIG. 103C are similar to components shown in FIG. 103B, asindicated by similar reference numbers.

The CI decoder applies one or more decode signals to the receivedbaseband signal. If the received baseband signal is coded with one ormore codes including complex conjugates of the one or more decodesignals, a sum of decoded baseband symbols over a code period combinescoherently. The combined symbols have a value associated with one ormore information signals. The combined symbols may be provided as a dataoutput after one or more optional signal-processing operations.

Symbols generated by the CI decoder 10302 are optionally processed inprocessor 10319 prior to being coupled to a transmission system 10306for re-transmission. CI-encoded signals not corresponding to complexconjugates of at least one of the decode signals (i.e., not intended forthe transceiver) contribute a substantially zero value to the combinedsymbols. The processor 10319 may be adapted to remove one or more signalcomponents intended for the transceiver. Since the signals intended forthe transceiver provide a dc offset to the individual symbols generatedby the CI decoder 10306, these signals may be removed by filtering,cancellation, or some other dc-removal process.

FIG. 104A illustrates a tree network that may be implemented in aspectsof the present invention. Transmissions passed to one or more nodes inthe network may be branched off, or routed, to a plurality of nodes.Routing may include processing any combination of network addressesconveyed in headers and network addresses conveyed by codes (e.g.,spreading codes, multiple-access codes, channel codes, etc.).

Network addresses may provide routing information and/or directions. Forexample, multiple addresses may convey one or more paths between asource node and a destination node. Various types of control informationmay be included in a code. For example, certain codes may conveypriority information or identify the type of data payload.

FIG. 104B illustrates a network design that permits a plurality ofcommunication paths to each node. Multiple network connections between asource node and a destination node may be provided for redundancy.Alternatively, each path may be selected based on one or more criteria,such as channel conditions and load balancing.

FIG. 104C illustrates a network design adapted to provide arrayprocessing performance advantages. A plurality of nodes 10426, 10427,10402, 10420, 10421, and 10422 are adapted to provide complex-weightedtransmissions to at least one destination node, such as nodes 10431 and10432. For example, a data sequence addressed to node 10431 is routed tonodes 10426, 10427, 10402, 10420, 10421, and 10422, which provideappropriate weights to the data transmission to generate a phase front10441 that converges at the destination node 10431. Similarly,appropriate delays or complex weights may be provided to transmissionsto produce a coherent phase front 10442 that converges at destinationnode 10432. Signals received by the nodes may be combined with respectto any combining technique, including optimal combining.

Nodes in a wireless network may generate weighted transmissions (orprocess received signals) to perform various types of array processing.Individual nodes may include one or more transceiver (e.g., antenna)elements. Array processing operations may include combinations of localand global processing. For example, diversity combining may be performedat each multi-element node and signals from each node may be combined ina central processor to perform sub-space processing. Other combinationsof local and global processing may be employed.

Array processing may include space-time processing, space-frequencyprocessing, beam forming, null steering, blind-adaptive processing, longbaseline interferometry, frequency-diversity interferometry, etc. Arrayprocessing may be performed to achieve any combination of sub-spaceprocessing (i.e., increased capacity) and diversity benefits (i.e.,improved performance). Selection of transmitting and receiving nodes inan array-processing network can be adapted to changing node positions,network loads, throughput requirements, user services, bandwidthavailability, frequency-reuse requirements, channel conditions, etc.

FIG. 105A illustrates a concentric ring network configuration in which abase station 10500 or access point provides direct or indirectcommunication links to a plurality of subscriber units 10501 to 10535arranged in a plurality of concentric-ring regions 10551 to 10553.Subscriber units 10501 to 10506 in region 10551 are adapted to routesignals to one or more subscriber units 10521 to 10535 in one or moreregions, such as region 10553. Similarly, subscriber units 10511 to10518 in region 10552 may be adapted to route signals to subscribers inother regions. In some applications, one or more subscribers may beadapted to route signals to at least one other subscriber in the sameregion.

Region shapes and sizes may be adapted to numbers of users and/or thegeographical distributions of the users. Similarly, regions may beadapted to balance network loads. For example, subscriber powerconsumption and processing requirements associated with routing signalsthrough subscribers near the base 10500 can be mitigated by distributingrouting operations over a larger number of subscribers. Thus,subscribers in regions 10551 and 10552 perform routing associated with adirect transmission from and/or to the base 10500. Similarly, the numberof subscribers in primary arteries of tree networks (or other networks)can be increased. Routing functions can be assigned to subscribers basedon subscriber location, subscriber load, channel conditions, and networkload. The network configuration illustrated in FIG. 105A may beintegrated with other network architectures, such as treeconfigurations.

FIG. 105B illustrates a network configuration adapted to the geographicdistribution of a plurality of subscribers 10521 to 10526 and 10531 to10536 located along a roadway. In this case, there are two routing paths10561 and 10562 provided by subscriber routing. Network configurations,including transmission paths, may be adapted to subscriber distributionsand channel conditions. For example, urban channel environments aretypically characterized by a waveguide grid. Thus, routing paths may beprovided with a grid architecture in urban areas.

A transmission may include multiple levels of coding intended to bestripped off at each node along a predetermined path to a particularaddress. FIG. 106A illustrates three nodes 10601, 10602, and 10604. Thefirst node is adapted to decode a one-rotation basic CI code by applyingcomplex-conjugate decoding of the one-rotation code. A basic CI codec_(m) characterized by m rotations (m<N) is expressed by the followingequation:

$c_{m} = {^{\; m\; \varphi^{\prime}}{\sum\limits_{n = 0}^{N - 1}{^{\; m\; n\; 2{\pi/N}}\hat{n}}}}$

The complex-conjugate decoding essentially unwinds the code. Similarly,nodes 10602 and 10604 are adapted to decode two-rotation andfour-rotation codes, respectively. For simplicity, the rotations areprovided in a common predetermined direction.

In one aspect of the invention, each node splits a received signal intoat least two signals. At least one of the split signals is decoded atthe node to extract any information intended for that node. A node maybe associated with one or more addresses, or codes. At least one splitsignal is passed through the node without any decoding. Thus, node 10601receives signals coded (or addressed) with one code rotation, node 10602receives signals coded (or addressed) with two code rotations, etc.

In another aspect of the invention, a signal input to a node is notsplit prior to being decoded to extract any signals intended for thatnode. The decoded signal is then re-encoded with respect to the complexconjugate of the decoding operation. Thus, any unwinding associated withdecoding is reversed prior to re-transmission of the coded informationsignal. Optionally, a node transceiver may cancel or otherwise removesignals addressed to itself prior to re-encoding.

In yet another aspect of the invention, coded transmissions are codedwith respect to the intended path(s) to a predetermined address, thusobviating the need for splitting or re-encoding. For example, aninformation signal addressed to nodes 10602 and 10604 input to the firstnode 10601 is encoded with a pair of basic CI codes having threerotations and seven rotations, respectively:

$r_{{node}\; 901} = {\sum\limits_{n = 0}^{N - 1}{\left( {{{s_{2}(t)}^{\; 3n\; 2\; {\pi/N}}} + {{s_{4}(t)}^{\; 7\; n\; 2\; {\pi/N}}}} \right)\hat{n}}}$

Decoding at the first node 10601 unwinds the coded signals by onerotation. The decode signal is characterized by C*(1), which is thecomplex conjugate of code C(1). Thus, node 10601 passes a codedinformation signal to node 10602 expressed by two-rotation andsix-rotation codes:

$r_{{node}\; 902} = {\sum\limits_{n = 0}^{N - 1}{\left( {{{s_{2}(t)}^{\; 2n\; 2\; {\pi/N}}} + {{s_{4}(t)}^{\; 6\; n\; 2\; {\pi/N}}}} \right)\hat{n}}}$

A sum of the decoded chips yields zero because there are no inputsignals coded with a single-rotation code. A sum of the chips generatedat node 10601 is zero because the non-zero rotations cause the chipvalues to cancel.

Decoding with decode signal C*(2) at node 10602 unwinds the codedsignals by two rotations. Thus, a sum of the decoded signal at node10602 coherently combines chip values associated with signal s₂(t). Node10602 produces a coded information signal expressed by:

$r_{{node}\; 904} = {\sum\limits_{n = 0}^{N - 1}{\left( {{s_{2}(t)} + {{s_{4}(t)}^{\; 4\; n\; 2\; {\pi/N}}}} \right)\hat{n}}}$

The values s₂(t) may optionally be removed (such as by cancellation,dc-offset removal, etc.) prior to transmission to node 10604. A nodetransceiver at node 10602 may ensure non-zero chip values prior totransmission.

Coded signals received by node 10604 are processed with acomplex-conjugate code C*(4) that unwinds the coded signal by fourrotations. The resulting decoded signal is expressed by:

$r_{{node}\; 904^{\prime}} = {\sum\limits_{n = 0}^{N - 1}{{s_{4}(t)}\hat{n}}}$

Decoding and summing the code chips at node 10604 coherently combinessignal values s₄(t) associated with a four-rotation code C(4).

FIG. 106B illustrates a simple tree-style CI-based network. Nodes 10601,10602, and 10604 are provided with decode signals corresponding toC*(1), C*(2), and C*(4), respectively. A branch node 10603 employs adecode signal C*(3) adapted to decode signals characterized by threerotations in a predetermined direction. A signal addressed with basic CIcodes corresponding to rotations of seven, three, and six are input tonode 10601. Signals output by node 10601 to node 10602 correspond torotations of six, two, and five. Node 10602 provides a decode signal ofC*(2) to its input signal. Thus, the input corresponding to tworotations is decoded and the resulting value is processed at the node10602. The resulting output signal(s) from node 10602 is expressed byrotations as four, zero, three. The zero value may characterize asubstantially null signal resulting from cancellation of the decodedsignal at node 10602.

Node 10602 may provide a broadcast signal to nodes 10603 and 10604.Alternatively, node 10602 may duplicate the signal four, zero, three andprovide a signal to each of the nodes 10603 and 10604. In some cases,node 10602 may be adapted to separate its input signal into a pluralityof components relative to addresses. Each component may be forwardeddirectly to its intended node. In some cases, separate signals may beprovided via beam forming. In other cases, some form of multiple access,including header addresses, may be employed.

FIG. 106C illustrates a simple multipath CI-based network. Node 10602 isprovided with coded signals (expressed in rotations as 2, 5, 6, 3, 4).The value two is addressed to node 10602. The values five and six areaddressed to nodes 10603 and 10604. A fourth node 10606 receivestransmissions from nodes 10603 and 10604. Thus, values three and fourcharacterize paths through nodes 10603 and 10604, respectively, that areaddressed to node 10606. Signals received and decoded at node 10606 maybe combined coherently. Such combining may include optimal combining.

In some aspects of the invention, node 10606 may be provided withadditional decode values (e.g., C*(5)) to enhance reception.Furthermore, two or more decode values (e.g., C*(6) and C*(5)) may beexploited in appropriate combinations to provide beam forming (orequivalent array processing) operations. Various combining operationsmay be provided to provide any combination of interference rejection,diversity enhancement, and sub-space processing (i.e., capacityenhancement).

FIG. 106D illustrates a plurality of nodes 10601 to 10605 and at leasttwo communication paths. A first communication path includes nodes10602, 10604 and 10605. A second communication path includes nodes10601, 10603, and 10605. In this case, the two paths illustratecommunication to node 5. Alternatively communication paths may beprovided indicating communications from node 10605.

Signals arriving from the first communication path are encoded with atleast one code c₁(n). Similarly, the signals arriving from the secondcommunication path are encoded with at least one code c₂(n). In variousapplications of the invention, additional communication paths (notshown) may be provided.

The codes c₁(n) and c₂(n) may be address codes or they may includeaddress codes. The codes c₁(n) and c₂(n) may be similar or different.Alternatively, the codes c₁(n) and c₂(n) may be separate (or different)from address codes. In some cases, address codes may be adapted toprovide additional coding or achieve other objectives, such as, but notlimited to, encryption, verification, authentication, identification,anti-jamming, and/or diversity benefits.

In one set of embodiments of the invention, redundant informationsignals or signals providing redundant information are routed along themultiple paths to the destination node 10605. This can provide diversitybenefits. The codes c₁(n) and c₂(n) may include similar or differentchannel codes. Signals provided along the multiple paths may be decoded(if necessary) and coherently combined in a receiver at the node 10605.Combining may include one or more optimal-combining techniques. Thenumber of transmission paths that are coherently combined isproportional to an effective processing gain of the combining process.Consequently, low-power information-bearing transmissions may beemployed over the multiple transmission paths. Signals received fromdifferent paths may be processed via soft-decision processing to provideconfidence measurements for symbol estimates and/or enhance channelcompensation and/or decoding.

In another set of embodiments, each of a plurality of signals routedalong different paths to a given node may provide necessary keys (orequivalent information) necessary for decoding. For example, signalsrouted along a first path may provide a coded information signal to apredetermined destination. Signals routed along a second path to thesame destination may provide a decode sequence to decode the codedinformation signal. The codes c₁(n) and c₂(n) may include codes that arecomplex conjugates of each other. The first code c₁(n) may include apublic key and the second code c₂(n) may include a private key whereinthe two codes c₁(n) and c₂(n) contribute the necessary code keys fordecoding a coded information signal transmitted along the first and/orsecond paths, or along a third path. Various pluralities of codes,paths, and/or coded information signals may be employed.

The process of providing multiple decoder keys across multipletransmission paths may be part of an authentication and/or verificationprocess. The codes c₁(n) and c₂(n) may include channel-specific codesthat characterize the channel between at least one transceiver and thedestination node 10605. The codes c₁(n) and c₂(n) may include channelcompensation. Consequently, a channel analysis of received signals atthe destination node 10605 will indicate the likelihood that the signalswere transmitted from known nodes, such as nodes 10603 and 10604.Similarly, channel analysis may be employed to determine the immediateoriginating node of a given transmission. The codes c₁(n) and c₂(n) mayinclude beam-forming weights.

In some aspects of the invention, channel estimation may be performed ona signal received from a transceiver attempting to access the network.Various location-finding processes (e.g., direction-of-arrivaldetermination, geo-location tracking, triangulation, etc.) may beimplemented to determine the transceiver's location relative to a set orrange of allowed locations. In some applications, identification ofunauthorized users may be combined with location finding.

FIG. 106E illustrates a node 10602 used in a plurality of crossingcommunication paths. Nodes 10601, 10602, and 10604 are part of a firstcommunication path. Nodes 10611, 10602, and 10613 are part of a secondcommunication path characterized by at least one unique diversityparameter value. In this case, the communication paths are distinguishedby different carrier frequencies. Alternatively, communication paths maybe differentiated by code, polarization, subspace, time, phase,subspace, or any combination thereof.

Although basic CI codes are illustrated in the exemplary networkarchitectures, other types of codes (including, but not limited to,complex CI codes, Walsh codes, multi-code sets, multi-level (or stacked)codes, and/or codes derived from invertible transforms) may beimplemented in the examples shown, as well as in variations,adaptations, permutations, and combinations of the exemplary networkarchitectures. Network address codes may be employed for one or moreadditional functions, including, but not limited to, spread spectrum,multiple access, channel coding, and encryption. Network designs shownin the figures and described in the specification are intended to conveybasic principles and various aspects of the invention. These networkdesigns do not limit the scope of the invention. Consequently, variousnetwork designs may be considered as building blocks for complex networkarchitectures.

Network designs and other aspects of the invention may be combined withprior-art network designs, systems, devices, protocols, formats, and/ormethods. Such combinations are clearly anticipated and suggested.Aspects and embodiments of the invention may serve as portions ofnetworks. Network designs, systems, and/or methods of the invention maybe adapted to various types of networks, such as long-haul, short-haul,last-mile, local-area, metropolitan-area, sensor, RF-identification,tracking, ad-hoc, mobile radio, personal communication, cellular,airborne, air-ground, and/or satellite networks. Network architecturesof the invention may include one or more types of multiple access.Network architectures of the invention may include any combination ofaddressing, including address codes and packet headers containingaddresses.

FIG. 107A illustrates a multi-level cellular architecture that may beemployed by systems and methods of the present invention. At least onemacro-cell 10721 is subdivided into one or more micro-cells 10731.Various multiple-access techniques may be used to separatecommunications in different cells. For example, a predetermined code maybe provided to transmissions within the macro-cell 10721. Macro-cellcodes may be provided for inter-cell multiple access or radio isolation.Micro-cell codes may be provided for intra-cell multiple access. Codesapplied to transmissions may implement additional network functions,such as spread spectrum, encryption, authentication, channel coding,addressing, and/or interference mitigation.

In some applications, multi-level codes may be implemented. In somecases, macro-cell codes may provide greater processing gain than themicro-cell codes. For example, macro-cell codes may consist of longcodes and micro-cell codes may consist of shorter channel codes and/ormultiple-access codes. Either or both micro-cell codes and macro-cellcodes may implement CI and/or CI-based coding. Coding may be implementedwith, or as part of, array processing.

FIG. 107B illustrates three cells 10721 to 10723 in a cellular networkof the present invention. Each cell 10721 to 10723 employs a differentlong code C_(L1) to C_(L3), respectively, to differentiate betweencommunications in adjacent cells. Each cell 10721 to 10723 providesintra-cell communications with codes C_(s1-N) to differentiate betweensubscriber units in each cell. Coding may include CI and/or CI-basedcodes. Additional multiple-access techniques may be employed to providefor inter-cell and intra-cell multiple access.

FIG. 107C shows a cellular architecture of the present invention thatincludes a plurality of cells 10721 to 10725 and a plurality of basestations 10701 to 10705 located on cell boundaries. The base stations10701 to 10705 may include spatially sectorized antennas to providecommunication to a plurality of cells. For example, base 10702 may beadapted to service users in cells 10721, 10722, and 10723.

The base stations 10701 to 10705 may be adapted to route codedinformation across multiple cells. For example, coded data and/orcontrol information is routed from base 10702 to base 10703. A codedsignal may be duplicated or decomposed for routing to multiple bases orsubscriber units. For example, base 10703 transmits coded information tobases 10704 and 10705. In some applications, subscriber units, such assubscriber units 10711 and 10712 may be employed to route informationbetween two or more base stations. In any of the implementations of theinvention, transmission paths through a network may be selected based onone or more criteria, including transceiver availability, transceiverlocations, network loads, channel conditions, transmission-powerrequirements, etc.

FIG. 107D illustrates a cellular network of the invention including aplurality of cells 10721 to 10730, a plurality of base stations 10700 to10709, and a plurality of subscriber units, such as subscriber units10761 to 10763 and 10771 to 10773. In this case, the bases 10700 to10709 are located inside each cell 10721 to 10730. Other cellulararchitectures may be employed.

A base station (e.g., base 10700) may route information directly toother bases (e.g., bases 10701, 10702, 10704, 10705, and 10706). Suchdirect transmissions paths are indicated by transmission paths 10741 to10745. A direct transmission path l0746 may be provided to a base (suchas base 10709) that is not adjacent to the originating base 10700. Atransmission between bases may be routed through intermediate bases. Forexample, base 10705 acts as a router for transmissions between base10700 and bases 10707 and 10708. Similarly, subscriber units (such assubscriber units 10771 and 10772 may be employed as routers forcommunications between bases (e.g., bases 10700 and 10703), betweensubscribers, and/or between bases and subscribers.

FIG. 108A illustrates a method for providing CI-coded transmissions ofinformation and control signals. The method described in FIG. 108A maybe performed by a subscriber unit acting as a base station in a CInetwork. A CI code generation process 10801 provides CI codes and/orCI-based codes for at least one information signal and at least onecontrol signal. A control signal may provide for one or more controlfunctions, such as, but not limited to, power control, synchronization,code assignments, priority assignments, link assignments, channelassignments, duplexing control, training-signal generation, notice oftransfer of control responsibilities, and request acknowledgement.Coding processes 10802 and 10803 encode the information signal(s) andcontrol signal(s), respectively. A transmission process 10804 providesfor transmission of the coded signals.

FIG. 108B illustrates a method for managing network control in a CInetwork by one or more subscriber units adapted to function as basestations. A CI transceiver acting as a base station transmits CI-codedinformation and control signals in a transmission step 10810. In anetwork identification and communication restriction step 10811, CIcodes can be used, at least in part, to address the communication andcontrol channels. CI codes can be allocated to restrict communicationsbetween transceivers permitted to operate in the network. CI codes canalso be used to identify a radio network and each of the radio devices,as well as the type of communications being transmitted.

A duplexing step 10812 provides for management of transmission andreception. Various types of duplexing may be employed, such astime-division duplexing, frequency-division duplexing, code-divisionduplexing, polarization-division duplexing, etc. A CI transceiver mayinclude a plurality of CI decoders in parallel to allow reception ofmore than signal simultaneously. Similarly, transmission of codedsignals may be performed simultaneous with reception when thetransmitted CI codes differ from the code of the received signal.Furthermore, different CI codes may be used to encode transmissions todifferentiate types of transmitted signals.

A network-control step 10813 indicates that at least one of thesubscriber units becomes a network control station. A network controlstation initiates communications and maintains power control and timesynchronization of the network in the same manner that a base stationwould normally function. A transfer step provides for transfer ofnetwork control from at least one subscriber to at least one differentsubscriber. The network control station can voluntarily transfer, or becommanded to transfer, power control and time synchronization of thenetwork to any other radio in the network.

FIG. 108C illustrates a network-control method of the present invention.A CI coding step 10821 provides different CI codes (such as may be usedto spread a signal) to information and control signals. A networkcontrol station may provide time-division duplexing 10822 to regulatetransmission and reception. A network-control step 10823 provides fornetwork control by the network control station. Network control caninclude various operations, including, but not limited to,synchronization, power control, code assignment, channel assignments,channel coding, transmission-path selection, load balancing, andspectrum management.

FIG. 108D shows a routing method of the present invention. A coding step10831 provides a multi-address, CI-coded signal for transmission in atransmission step 10832. The addresses may be provided by anycombination of CI coding and header addressing. Transmitted signals maybe routed via one or more paths through a network. A duplication step10833 is provided when transmission paths through a node diverge.Duplicated signals are transmitted along their respective paths.

FIG. 109A shows a relay method of the present invention. Received signalare decoded in a decoding step 10901 at each node. The decoding step10901 involves applying a code to a received signal corresponding to thecomplex conjugate of the node's address code. A processing step 10902processes information signals coded with the node's address codes.Processing 10902 may include summing the decoded symbols and performinghard and/or soft decisions. Information signals addressed to the nodeprovide a dc offset to the symbols of the decoded signal. This offsetmay optionally be removed 10903 prior to transmitting 10905 theresulting decoded signals.

FIG. 109B illustrates an alternative embodiment of a relay method of theinvention. Some of the steps in the relay method shown in FIG. 109B aresimilar to the steps shown in FIG. 109A, as indicated by similarreference numbers. A reverse-decoding step 10904 provided between steps10903 and 10905 applies the complex conjugate of any codes applied tothe received signals in the decoding step 10902.

FIG. 110A illustrates a transceiver processing and routing method of theinvention. A decoding step 11001 processes received signals with atleast one complex-conjugate code corresponding to at least one addresscode associated with the transceiver address and/or one or morepredetermined addresses. Decoding 11001 may include one or more decodingprocesses, such as channel decoding, multiple-access decoding,spread-spectrum decoding, and decryption. The decoding step 11001 mayoptionally include a level-detect function (not shown) to verify that areceived signal is present prior to decoding.

A processing step 11002 is adapted to provide one or moresignal-processing steps to the decoded signals. The processing step11002 may estimate the values of information or control signalsimpressed onto address codes corresponding to the complex-conjugatecode(s) provided in the decoding step 11001. For example, an adding step(not shown) may provide for coherent combining of addressed informationsymbols. A decision step (not shown) may follow the adding step (notshown). If any signal values are present, they may be passed to anoptional error detection/correction step 11011.

Error detection/correction 11011 may employ parity checks, trellisdemodulation, convolutional decoding, block decoding, and/or any otherchannel decoding or error-checking technique. Errors may be correctedvia receiver-side processing. Alternatively, error detection mayinitiate a request for re-transmission. Error detection/correction 11011may include re-quantization, channel estimation, channel compensation,predistortion of transmissions, multi-user detection, and/or optimalcombining. Error detection/correction 11011 may include decisionprocessing, including hard decisions and/or soft decisions. Decisionprocessing may include iterative feedback processing, such as turbodecoding.

The signal values may be provided to an optional system-function step11012. Confidence measures from soft-decision processes may be used toadapt receiver parameters (e.g., the processing step 11002), such as tooptimize reception. Similarly, received control information may be usedto adjust receiver parameters. System functions 11012 may includeautomatic gain control, adapting filter parameters, adjustingquantization constellations, and/or changing sampling parameters. Systemfunctions may also include removing symbols or values associated withone or more predetermined addresses from the input signal values.

The signal values may be provided to an optional network-function step11013. Network functions 11013 may be selected or adapted relative toreceived control information. Network functions 11013 may includerouting, addressing, power control, synchronization, requestre-transmission, multiple-access control, channel selection,authentication, verification, identification, link-priority assignments,load balancing, spectrum management, and/or error processing. Networkfunctions 11013 may include adding, removing, and/or changing systemcontrol information.

Data and control information are re-encoded in a coding step 11004.Re-encoding 11004 may include the application of one or more codes,including address codes, multiple-access codes, spreading codes, channelcodes, and encryption. Coded signals are processed for transmission intoa communication channel in a transmission step 11005.

FIG. 110B illustrates a transceiver processing and routing method of theinvention. A received signal is duplicated in a duplication step 11000.At least one duplicated signal is coupled into a decoding step 11021that applies a complex-conjugate code to the received signal. Thecomplex-conjugate code is related to the address code of thetransceiver. The decoded signal is processed in a processing step 11022to extract or otherwise estimate information values addressed to thetransceiver.

At least one of the duplicated signals is input to a secure procedure11010. For example, the at least one duplicated signal is passed througha fire wall (not shown). A decoding step 11016 provides for decodingsignals addressed to one or more destinations other than the currenttransceiver. A processing step 11018 is adapted to provide one or moresignal-processing steps to the decoded signals. The processing step11018 may estimate the values of information or control signalsimpressed onto address codes corresponding to the complex-conjugatecode(s) provided in the decoding step 11010.

Processed signals may be coupled to one or more optional processingsteps, including error detection/correction 11011, system function11012, and network function 11013 steps. The processed signals areencoded 11014 prior to being transmitted 11005. Similarly, data input tothe transceiver is encoded 11024 prior to being transmitted 11005.

FIG. 111A illustrates a method of receiving, processing, andre-transmitting signals. A receiving process 11101 provides reception ofone or more signals received from one or more communication channels(not shown). The received signals are sampled in a sampling process11103 with respect to a plurality of sampling parameters that areselected 11102 or predetermined.

Sampling parameters may include sample width, sample rate, sampleduration, sample shape, and/or number of samples per symbol. One or moresampling parameters may be selected relative to characteristics of thereceived signal(s). For example, a multicarrier signal may be sampled insuch a way as to generate symbols corresponding to the receivedsub-carrier channels. Alternatively, a single-carrier signal may besampled with respect to a CI-signal generation algorithm adapted togenerate a plurality of CI components from the single-carrier signal.Other signal characteristics that may be used to determine samplingparameters include carrier frequency, bandwidth, signal strength, noise,and/or interference levels.

The samples are provided for CI processing 11104 to generate a pluralityof CI components. CI-component generation 11104 may include a Fouriertransform operation. CI components may include CI signals and/or CIsignal values. The CI components are combined in a combining process11105 that may include a plurality of parallel combining processes. Thecombined CI components produce data symbols, such as data symbolsindicative of high-rate, broadband, symbols received from asingle-carrier signal.

The data symbols are processed in a data symbol processing step 11106that may include one or more signal-processing steps 11110, including,but not limited to, symbol analysis, symbol blocking, symbol insertion,interception of symbols, symbol-stream and/or packet addressing, symbolredirection, and/or symbol generation. The data symbol processing step11106 may include a plurality of parallel processes. For example, aplurality of parallel low-speed CI combining processes that produce aplurality of data symbols can be coupled to a plurality of low-speed,data symbol processing steps.

A CI component generation step 11107 provides for generation of aplurality of CI components from the processed data symbols.Alternatively, a parallel-to-serial process (not shown) may be employedto generate a high-rate data-symbol sequence that is coupled to atransmission system 11108. In the present example, CI components areprovided to the transmission system 11108 for processing and couplinginto at least one communication channel (not shown). The CI componentsmay be processed with an inverse-Fourier transform to generate ahigh-rate, time-domain signal.

FIG. 111B illustrates a system adapted to receive, process, andre-transmit signals according to the method outlined in FIG. 111A. Areceiver system 11121 processes transmitted signals received from one ormore communication channels (not shown). The processed signals mayoptionally be filtered by an anti-aliasing filter 11122 prior to beingcoupled into a sub-carrier generator, such as a Fourier transformprocessor 11123. CI components generated by the processor 11123 areprovided to a combining system 11124 to generate a plurality of datasymbols. The combining system 11124 may include a plurality of combinersadapted to operate in parallel. Similarly, a data processor 11125 may beadapted to process the data symbols via a plurality of simultaneousparallel operations.

A CI symbol generator 11126 generates a plurality of CI symbols from theprocessed data symbols. The CI symbols are impressed onto a plurality ofcarriers, such as by an inverse Fourier transform 11127, which generatesa high-rate, time-domain signal. Alternative one or more systems may beemployed that generate a high-rate data stream from the processed datasymbols. The data stream is provided to a transmission system 11128adapted to process the data stream for transmission into at least onecommunication channel (not shown).

SCOPE OF THE INVENTION

In the preferred embodiments, several kinds of carrier interferometry,coding, filtering, and spatial processing are demonstrated to provide abasic understanding of applications of CI processing. With respect tothis understanding, many aspects of this invention may vary. Forexample, signal spaces and diversity parameters may include redundantlymodulated signal spaces. Descriptions of spatial processing may beapplied to processing methods for non-spatial diversity parameters.Descriptions of systems and methods using spatial subspaces may beextended to systems and methods that use non-spatial subspaces.

For illustrative purposes, flowcharts and signal diagrams represent theoperation of the invention. It should be understood, however, that theuse of flowcharts and diagrams is for illustrative purposes only, and isnot limiting. For example, the invention is not limited to theoperational embodiment(s) represented by the flowcharts. The inventionis not limited to specific signal architectures shown in the drawings.Instead, alternative operational embodiments and signal architectureswill be apparent to persons skilled in the relevant art(s) based on thediscussion contained herein. Also, the use of flowcharts and diagramsshould not be interpreted as limiting the invention to discrete ordigital operation.

In practice, as will be appreciated by persons skilled in the relevantart(s) based on the discussion herein, the invention can be achieved viadiscrete or continuous operation, or a combination thereof. Furthermore,the flow of control represented by the flowcharts is provided forillustrative purposes only. As will be appreciated by persons skilled inthe relevant art(s), other operational control flows are within thescope and spirit of the present invention.

Exemplary structural embodiments for implementing the methods of theinvention are also described. It should be understood that the inventionis not limited to the particular embodiments described herein. Alternateembodiments (equivalents, extensions, variations, deviations,combinations, etc.) of the methods and structural embodiments of theinvention and the related art will be apparent to persons skilled in therelevant arts based on the teachings contained herein. The invention isintended and adapted to include such alternate embodiments. Suchequivalents, extensions, variations, deviations, combinations, etc., arewithin the scope and spirit of the present invention.

Signal processing with respect to sinusoidal oscillating signals aredescribed herein. Those skilled in the art will recognize that othertypes of periodic oscillating signals that can be used, including, butnot limited to, sinusoids, square waves, triangle waves, wavelets,repetitive noise waveforms, pseudo-noise signals, and arbitrarywaveforms.

The foregoing discussion and the claims that follow describe thepreferred embodiments of the present invention. With respect to theclaims, it should be understood that changes can be made withoutdeparting from the essence of the invention. To the extent such changesembody the essence of the present invention, each naturally falls withinthe breadth of protection encompassed by this patent. This isparticularly true for the present invention because its basic conceptsand understandings are fundamental in nature and can be broadly applied.

1.-8. (canceled)
 9. A method for providing communication signalsaccording to operating parameters using CI, said operating parametersincluding symbol duration, guard time interval, number of CI carriers,carrier-frequency spacing, carrier-frequency offset, and number of bitsper symbol per CI carrier, said method comprising the step of: receivinga feedback signal from a receiver; determining that an operatingcharacteristic of said method should be scaled from a first level to atleast a second level based on said feedback signal received from saidreceiver, said operating characteristic including at least one oftransmission rate, signal-to-noise ratio, probability of error, anddelay-spread tolerance; and dynamically scaling at least one of saidoperating parameters for said method to achieve an operatingcharacteristic of said second level by adaptively selecting one of aplurality of operating parameter scaling options in accordance with saiddetermining step.
 10. A CI system adapted to provide communicationsignals according at least one operating parameter of a set includingsymbol duration, guard time interval, number of CI carriers,carrier-frequency spacing, carrier frequency offset, and number of bitsper symbol per CI carrier, said system comprising: dynamic controlcircuitry adapted to receive a feedback signal from a receiver anddetermine whether at least one operating characteristic of said methodshould be scaled from a first level to a second level based on saidfeedback signal, said at least one operating characteristic including atleast one of transmission rate, signal-to-noise ratio, probability oferror, and delay-spread tolerance, and, after determining that saidoperating characteristic for providing communication signals should bescaled from said first level to said second level based on said feedbacksignal, provides at least one control signal, and signal circuitryadapted to be responsive to the at least one control signal todynamically scale at least one of said operating parameters to achievesaid operating characteristic of said second level, said controlcircuitry controlling at least one scalable operating characteristic byadaptively selecting at least one of a plurality of operating parameterscaling options.
 11. A CI-code generator adapted to generate at leastone CI code, the CI-code generator including: a CI-symbol generatoradapted to generate a plurality of CI symbols, and a symbol combinercoupled to the CI-symbol generator, the symbol combiner adapted toselect least one set of the CI symbols to generate at least one CI code.12. The CI-code generator recited in claim 11 wherein the CI-symbolgenerator further includes a code processor adapted to process at leastone set of CI-based symbols with at least one other symbol set togenerate the plurality of CI symbols.
 13. The CI-code generator recitedin claim 12 wherein the code processor is adapted to process at leastone set of CI-based symbols with at least one code of a code setincluding spread-spectrum codes, multiple-access codes, channel codes,sub-channel codes, encryption codes, multi-level codes, compressioncodes, hybrid codes, and CI codes.
 14. A CI transmitter adapted toencode at least one information signal with at least one CI code, the CItransmitter including: a CI-code generator adapted to generate at leastone CI code, a CI encoder coupled to the CI-code generator, the CIencoder adapted to impress at least one information signal onto the atleast one CI code to generate at least one CI-encoded signal, and atransmission system coupled to at least one communication channel and atleast one of the CI-code generator and the modulator, the transmissionsystem adapted to process the at least one CI-encoded signal fortransmission into the at least one communication channel.
 15. The CItransmitter recited in claim 14 wherein the CI-code generator is adaptedto generate at least one code of a code set including a multiple-accesscode, a spreading code, a channel code, an encryption code, asub-channel code, an error-correction code, a hybrid code, a multi-levelcode, and a compression code.
 16. A transmitter for a communicationsystem including: a CI coder adapted to generate a plurality ofalgebraically unique linear combinations of a plurality of informationsignals, and a modulator adapted to impress each of the linearcombinations onto a plurality of diversity-parameter values.
 17. A CIcoder including: a CI-code generator capable of generating a pluralityof CI codes, a modulator adapted to modulate a plurality of informationsignals onto a plurality of the CI codes, and a CI symbol generatoradapted to combine a plurality of information-modulated CI-code chips togenerate a plurality of CI symbols.
 18. A CI decoder including: an inputadapted to provide a plurality of received CI symbols, a CI-codegenerator capable of generating at least one reference CI code, and acombiner adapted to combine the received CI symbols relative to the atleast one reference CI code to generate at least one estimatedinformation signal.
 19. A transmitter system including: a CI signalgenerator adapted to produce a plurality of information-bearing CIsymbols distributed over at least a first set of diversity-parametervalues, and a multi-element transmitter adapted to distribute the CIsymbols over at least a second set of diversity-parameter values.
 20. Atransmitter system including: a CI-symbol generator adapted to generatea plurality of information-bearing CI symbols, a weighting systemadapted to provide at least one weight to at least one of the CI symbolsto perform at least one of a set of functions including time-domainshaping, frequency-domain shaping, crest-factor reduction, encryption,beam forming, and channel compensation, and a modulator adapted toimpress the weighted CI symbols onto at least one set ofdiversity-parameter values.
 21. A method of generating CI signalsincluding: providing for channel estimation, providing for generating aplurality of CI carriers, and providing for pre-transmission processingof the CI carriers to provide channel compensation.
 22. Asoftware-defined CI transmitter including: at least one hardwarecomponent including at least one computer processing unit and at leastone memory device adapted to support at least one software applicationprogram, and at least one software module including at least oneapplication program adapted to perform carrier selection and carrierweighting such that a superposition of the weighted carriers is providedwith at least one of a set of predetermined signal parameters, the setincluding formatting, source coding, encryption, sub-channel coding,channel coding, multiplexing, modulation, spread-spectrum coding, andmultiple-access coding.
 23. A filter including: a sampler adapted tocollect a plurality of samples of at least one band-limited signal, anda combiner adapted to combine a plurality of the samples with respect toat least one function generated from a superposition of subcarriers. 24.A filter including: a sampler adapted to generate a plurality of samplesof at least one band-limited signal, the sampler provided with at leastone predetermined sample rate and at least one predetermined samplewidth, and a combiner adapted to combine a plurality of the samples withrespect to at least one function representing a superposition ofsubcarriers, the combiner provided with at least one predetermined timeinterval over which the samples are combined.
 25. A CI transmitterincluding: a step-function generator adapted to generate at least onemulticarrier signal, a modulator adapted to impress at least oneinformation signal onto at least one multicarrier signal, and a filteradapted to band-limit the at least one information-modulatedmulticarrier signal.
 26. A CI transceiver including: a CI transceiversystem having at least one controllable transceiver-operationcharacteristic, at least one control circuit coupled to the CItransceiver system, the at least one control circuit adapted to controlat least one CI signal parameter, the at least one control circuit beingresponsive to at least one of a set including system requirements andchannel characteristics.